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X-WR-CALNAME:EE
X-ORIGINAL-URL:https://ee.iisc.ac.in
X-WR-CALDESC:Events for EE
BEGIN:VTIMEZONE
TZID:Asia/Kolkata
BEGIN:STANDARD
TZOFFSETFROM:+0530
TZOFFSETTO:+0530
TZNAME:IST
DTSTART:20220101T000000
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END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230327T210000
DTEND;TZID=Asia/Kolkata:20230327T230000
DTSTAMP:20260404T012223
CREATED:20230326T224428Z
LAST-MODIFIED:20230326T225234Z
UID:240559-1679950800-1679958000@ee.iisc.ac.in
SUMMARY:Thesis Defense of Mr. Manish Tathode
DESCRIPTION:Title:  Fast and Compact Voltage Equalizer for Satellite Applications. \nAdvisor: Prof. Vinod John.Date and Time: Monday\, 27th March 2023\, 3.30 pm.Location: EE-B304\, EE Department.Meeting Link: \nAbstract:Lithium-ion batteries have now become an inevitable constituent of the Electrical Power System of solar-powered satellites due to their high energy density\, wider operating temperature range\, and better radiation tolerance. For the compact realization and better space utilization\, the series-parallel connected Li-ion batteries are operated with currents close to the design limit of the cells\, speeding up the increase in the inherent initial imbalance in the individual cell voltages in a series-connected stack\, demanding fast equalization to avoid underutilization and reduced lifetime. Active multicell-to-multicell equalization achieves fast equalization by efficient simultaneous charge transfer among multiple cells in the series connected stack. PS-MAHB equalizer is one such multicell-to-multicell equalizer with the ability to maintain higher equalization currents irrespective of decreasing differences in the cell voltages. Its open loop\, soft-switched operation\, and modularization abilities make it an attractive choice for space applications. However\, it needs to be modified with the necessary protective features and required redundancy essential for its use in space applications. Hence\, the Modified PS-MAHB (M-PS-MAHB) equalizer is developed by incorporating necessary protection features and redundancy in the PS-MAHB equalizer. The flow of development of M-PS-MAHB equalizer is discussed. The Failure Mode Impact Analysis of the M-PS-MAHB equalizer reveals that during the most likely switch short circuit failure mode\, the faulty part of the equalizer is disconnected by the protective device and the redundancy does not let the cell get out of the equalization. Simulation results of FMIA considering transient and steady state impact of the failure are discussed.The existing static phase shift-based control of the equalizer causes direct dependency of the equalization currents on the cell voltages and limits the equalization current levels to lower than the design equalization current value when the cell voltages are lower. Thus\, the control works with a reduced rate of equalization and causes the under-utilization of the equalizer hardware for a significant duration of time in the charge-discharge cycle. A dynamic phase shift-based control is proposed to maximize the equalization current through the cells irrespective of the cell voltages which further increases the rate of equalization and improves the equalizer hardware utilization. In the simulation\, a significant improvement in the equalization rate compared to the static phase shift control is verified with the proposed dynamic phase shift-based control.The compact hardware realization of the equalizer hardware and the voltage sensor board addresses the space-volume constraints put by satellite applications. The equalizer hardware is realized as 4-cell equalizer modules\, and the compactness of the equalizer hardware is achieved by pushing the switching frequency to 1MHz reducing the values of the passive components. A non-isolated high-precision op-amp-based voltage sensing scheme is developed to target the equalization band close to 10mV. The concept of an easy-to-design motherboard-based interface is introduced\, which does not require any changes in the design of the 4-cell equalizer module and the voltage sensor board\, irrespective of the cell connector geometry.The experimental results verify the operation of the equalizer demonstrating the convergence of cell voltages from the initial imbalance of 300mV to the band of 10mV. The impact of the non-ideal dynamic response of the Li-ion cell voltage to a step change in current and its impact on the voltage-sensing-based control algorithm is discussed along with the necessary modifications brought in the control to reduce the impact.We request your presence at the thesis defence.
URL:https://ee.iisc.ac.in/event/thesis-defense-of-mr-manish-tathode-330pm/
LOCATION:EE-B304\, EE Department.
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230310T163000
DTEND;TZID=Asia/Kolkata:20230313T183000
DTSTAMP:20260404T012223
CREATED:20230309T234144Z
LAST-MODIFIED:20230309T234240Z
UID:240537-1678465800-1678732200@ee.iisc.ac.in
SUMMARY:MTech (Research) Colloquium of Vishwabandhu Uttam
DESCRIPTION:Title: A Unified Modeling Approach for Design and Performance Improvement of Triple Active Bridge Converter\n\nResearch Supervisor: Vishnu Mahadeva Iyer\n\n Meeting link\n\nAbstract:Triple Active Bridge (TAB) converter is a multi-port DC-DC converter. This converter is an extension of the popular Dual Active Bridge converter. It features desirable traits of the DAB converter\, such as high power density\, galvanic isolation\, and bi-directional power flow between any of the ports. As in other multi-port converters\, redundant power conversion is minimized through component sharing among the ports in a TAB converter. All the switches in a TAB converter can undergo soft-switching over a wide range of operating points\, reducing switching losses and the size of auxiliary components. The multiple degrees of freedom in modulating a TAB converter offer several design and operational flexibilities.However\, this converter has yet to come into the limelight despite these advantages. One of the reasons is the lack of a unified analytical framework for the design and operation of this converter. The existing models for the TAB converter are limited in scope and cannot be easily used for the design and operational optimization of the converter. This work focuses on developing simple\, unified models for analyzing the TAB converter.Firstly\, the popular Fundamental Harmonic Approximated (FHA) large-signal and small-signal models are evaluated to understand their limitations. Improved large-signal and small-signal Generalised Harmonic Models (GHM) are developed by incorporating the impact of higher-order harmonics. While the GHM is shown to be superior for small-signal analysis of the converter\, it is not suitable to analyze the soft-switching bounds of the TAB converter. To overcome the limitations of GHM\, a Unified Model that incorporates the impact of the magnetising inductance of the three-winding transformer is proposed. The Unified Model can accurately predict the AC port currents at the switching instants and is used to study the soft-switching bounds of the TAB converter. The GHM and Unified Model are validated through extensive switching circuit simulations and experimental results from a 1 kW hardware prototype developed in the laboratory.Further\, a new design algorithm for the TAB converter is proposed. The proposed algorithm leverages the FHA model’s simplicity and the Unified Model’s accuracy. Finally\, a new modulation scheme based on Penta Phase Shift with five degrees of freedom is proposed to achieve soft-switching across the operational range of the TAB converter.\nWe request your presence at the colloquium.\nAll are welcome.
URL:https://ee.iisc.ac.in/event/mtech-research-colloquium-of-vishwabandhu-uttam/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230309T143000
DTEND;TZID=Asia/Kolkata:20230310T043000
DTSTAMP:20260404T012223
CREATED:20230308T225946Z
LAST-MODIFIED:20230309T000550Z
UID:240527-1678372200-1678422600@ee.iisc.ac.in
SUMMARY:Thesis Defense of Shubham Rawat
DESCRIPTION:Title: A Novel Passive Regenerative Snubber for the Phase-Shifted Full-Bridge Converter:  Analysis\, Design and Experimental Verification. \nResearch  Supervisor: Prof. Kaushik Basu \nMeeting Link \n\nAbstract: \nThe development of Wide Bandgap (WBG) devices has enabled power electronic converters to operate at much higher frequencies\, voltages and power. Working at a higher switching frequency minimises the size of magnetics but results in significant switching losses and electromagnetic interference (EMI) noise. Thus\, it necessitates the use of soft-switching techniques to reduce these losses. Phase-Shifted Full-Bridge (PSFB) Converter is the most widely used soft-switching topology in the high-voltage and high-power\, unidirectional DC-DC conversion. The phase shift PWM control utilises the converter parasitic to achieve zero voltage switching (ZVS) turn ON. The gating technique allows the magnetic energy stored in the leakage inductance of the isolation transformer to charge and discharge the output capacitances of the inverter leg. \n\nHowever\, the converter suffers from severe voltage overshoots across the rectifier bridge during the zero to the active state transition. The resonant circuit formed between the transformer leakage inductance and the parasitic diode capacitance of the rectifier is responsible for the high-voltage ringing.  Many passive and active snubbers are presented in the literature to mitigate the high voltage overshoots across the diode bridge. While passive snubbers are relatively simple to implement than active snubbers\, they are lossy. On the other hand\, the active snubbers require additional gate driver circuitry and complex control. \nThe first part of the thesis proposes a novel passive regenerative snubber to overcome the mentioned drawbacks of the existing snubbers. The proposed snubber is ideally lossless with no control complexity. The work covers a detailed analysis of the PSFB operation with the proposed snubber while obtaining closed-form expressions for the converter state variables at the end of each topological stage. The study considers all the major converter parasitic\, such as transformer leakage and magnetising inductances\, and parasitic capacitances of the converter. Given the new snubber\, the thesis also lays out a step-by-step PSFB design procedure utilising the analysis carried out in the first part of the work. The design aimed to develop a 100 kHz PSFB for an input voltage of 360-400 V and the output power range of 0.5-1.5 kW at a fixed output voltage of 48 V. The design approach focuses on the two design objectives. All inverter switches must achieve ZVS turn ON\, and the converter gain must achieve the necessary gain to maintain desired constant output voltage for all possible operating conditions. \nA hardware prototype is built and tested as per the given specification. The experimental results validate the effectiveness of the snubber in reducing the voltage overshoot. Further\, the analysis and design accuracy is verified using the measured state variables. Finally\, the work presents the overall efficiency and the loss distribution among the converter components.
URL:https://ee.iisc.ac.in/event/thesis-defense-of-shubham-rawat/
LOCATION:Online\, India
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230304T143000
DTEND;TZID=Asia/Kolkata:20230304T223000
DTSTAMP:20260404T012223
CREATED:20230226T231315Z
LAST-MODIFIED:20230301T001554Z
UID:240474-1677940200-1677969000@ee.iisc.ac.in
SUMMARY:Open Day 4th March 2023
DESCRIPTION:Events are to be held in the Electrical Engineering Department on an open day. \nSPECTRUM  LAB DEMOS \nGenerative Models\, XAI for Optical Coherence Tomography\, AI Assisted Wireless-Capsule Endoscopy Analysis\, Neuromorphic Cameras\, Foreign Object Debris (FOD) Detection\, Real Time Human Pose Detection\,How to get into IISc?\, AI-assisted echocardiography                      Spectrum Lab at Open Day \nCOMPUTER VISION \nImage Analysis and Computer Vision Laboratory                                                                        IACV_Lab_Poster \nCONTROL SYSTEM \nReinforcement Learning Aided Efficient and Distributed Planning for Multi-Agent Systems                   cns-pt_open-day-2023 (3) \nDIGITAL SIGNAL PROCESSING \nINDIAN SIGN LANGUAGE\, AI VS HUMAN\, RPS GAME\, NON-CONTACT MEASUREMENT                    DSP Open Day Poster \nPower SYSTEM \nPOWER SYSTEM OPERATION AND CONTROL                                                   FIST_Lab_Open_Day23_Poster \nSignal Processing Interpretation and Representation (SPIRE) Lab\n\nWatch Me Speak                                                                                                      Demo1 \nMake computer speak in Indian Languages                                                             Demo2 \n Wanna be a sound engineer?                                                                                  Demo3 \nCan your breath sound reveal your gender?Mystery                                               Demo4 \nSpeed up to launch up!                                                                                             Demo5 \n Mimic your favorite actor                                                                                         Demo6 \nDo you hear what they say?                                                                                    Demo7 \nVisualize your vocals                                                                                              Demo8 \nCan you recognize correct pronunciation of an English word?                              Demo9. \nLanguage engineering and processing Lab \nAuditory perception Illusions                                                 LEAP_openday_BAI_2023 \nWho spoke when in a conversation?                                    openday_diarization_poster \nMultimodal Conversational Emotion Recognition                 open_day2023_soumya \nSound Based COVID-19 Diagnosis                                     open_day_poster2023_COSWARA \nAutomatic Speech Recognition                                            Introduction_To_ASR_Srikanth
URL:https://ee.iisc.ac.in/event/open-day/
LOCATION:EE\, IISc
END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230223
DTEND;VALUE=DATE:20230226
DTSTAMP:20260404T012223
CREATED:20230207T233153Z
LAST-MODIFIED:20230208T002600Z
UID:240387-1677130200-1677302999@ee.iisc.ac.in
SUMMARY:International Workshop on Planar Magnetic Technology
DESCRIPTION: 
URL:https://ee.iisc.ac.in/event/planar-magnetic-technology/
LOCATION:IISc
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230222T143000
DTEND;TZID=Asia/Kolkata:20230222T163000
DTSTAMP:20260404T012223
CREATED:20230215T224825Z
LAST-MODIFIED:20230215T224825Z
UID:240431-1677076200-1677083400@ee.iisc.ac.in
SUMMARY:Thesis Defense of Tanmay Mishra
DESCRIPTION:Title: Development of A Reconfigurable Synchronous Machine Emulation Platform \nFaculty Advisor: Prof. Gurunath Gurrala. \nMeeting Link:Click here to join the meeting \nABSTRACT: \nStudying the dynamic behavior of non-linear complex power systems in a laboratory is very challenging. Early experimental platforms used micro-alternators to emulate the behavior of fixed steam turbine models. The micro-alternator is a three-phase synchronous generator with similar electrical constants (in per unit on machine rating) as those typically found in alternators in large power stations. It is an electrical scaled-down model of machines up to 1000 MW rating and is rated between 1 to 10 kVA. Researchers used these micro-machines up to the 90s to study large electric generators’ transient and steady-state performance. The Department of electrical engineering at the Indian Institute of Science (IISc) was also very active in experimental research in power engineering. The department still retained two-three kVA and one ten kVA micro-machine sets\, but the control panels of these machines became obsolete as the manufacturer of these machines Mawdsley\, London\, doesn’t exist anymore. Advancements in simulation software packages and real-time simulators have primarily replaced the experimental models of electric power systems worldwide. The push for green energy technologies worldwide due to climate concerns has increased the presence of power electronic converters in the power grids. Reduction of overall inertia\, frequent occurrence of electromechanical oscillations\, electromagnetic transients\, and control interaction modes has become a concern for the power grid operators. The need for understanding the physical insights of the oscillatory modes introduced by fast-acting power electronic converters\, the need for developing practically feasible control algorithms for mitigating the interaction modes\, and the need for developing dispatchability and grid support features like conventional generation sources have triggered the development of laboratory-scale experimental power grids across the world in the past decade. \n In this thesis\, initially\, an attempt is made to revive the existing three kVA alternator controls. An IGBT-based buck converter static excitation system has been developed for the micro-alternator. This exciter also incorporates several limiters which were non-existent in the old analog control panels. An under-excitation limiter\, over-excitation limiter\, and V/Hz limiter as per IEEE standard 421.5 have been designed to protect the micro-alternator during abnormal conditions such as overloading\, overheating\, and over-fluxing of the machine. The detailed tuning procedure of limiters and TCR is discussed to comply with IEEE STD 421.2 and IEEE STD 421.5. A digital time constant regulator (TCR) is incorporated to modify the micro-alternator’s field’s time constant to mimic large synchronous machines’ dynamics as micro-machine time constants are very small. A custom 5 kVA micro-alternator was manufactured through a local vendor having parameters like the Mawdsley machines to facilitate the creation of multiple short circuits in the testbed. \nA single micro-alternator can represent only one large alternator dynamics\, thereby limiting the platform’s scalability. Emulating machines of different ratings using a single micro-machine would undoubtedly boost the capabilities of experimental platforms for investigating conventional and nonconventional source interactions in laboratories. To the best of our knowledge\, only one such attempt was made in the literature\, where a model reference control algorithm is proposed to mimic any rating alternator dynamics using a doubly excited laboratory micro-alternator. However\, doubly excited micro-alternators are non-existent today. A generalized experimental platform using a non-linear output matching controller based on output feedback linearization is developed in this thesis for emulation of large turbo-alternators of different ratings\, IEEE STD 421.5 excitation systems\, and standard turbine governor models in the laboratory using the 5 kVA micro-alternator. IEEE Model 1.1 synchronous machine model in per unit on machine MVA rating with associated excitation system and governor-turbine models has been used as a reference model to be emulated. A single machine infinite bus (SMIB) setup with the 5 kVA micro-alternator and a 50 km 220 kV scaled lumped parameter frequency-dependent transmission line model is used for experimental validation. Synchronous generators of ratings\, 128 MVA\, 247.5 MVA\, and 1000 MVA have been physically emulated using the setup. The dynamic responses of the large machines with thermal turbines (reheat\, non-reheat)\, hydro turbine\, and excitation systems; DC1A\, AC4A\, and ST1C have been reproduced under small and large disturbances. \nA systematic scaling approach has been proposed to emulate a multi-machine system in the laboratory. Unlike in the SMIB system\, the power levels of generators in a multi-machine system should be scaled to the laboratory level for emulation. Hence\, every power system component (generator\, transmission lines\, transformer\, loads) is scaled to a uniform level so that the laboratory machines don’t get overloaded. The developed non-linear control strategy for emulation has been extended to multi-machine systems. The Western System Coordinating Council 3-generator 9-bus test system has been used to validate the proposed concept. The feasibility of replicating WSCC system dynamics in a laboratory as a scaled-down model has been verified through simulations under small and large disturbances. Emulating large machine dynamics with different types of turbines\, governors\, and excitation controls using a singly excited micro-alternator enabling a generalized synchronous machine emulation platform is a first-of-its-kind effort in the literature to the best of our knowledge. \n Note: Know how generated from the Source Emulation has been licensed to MCore Technologies Pvt Ltd\, Bangalore for commercialization. \nAcknowledgments: This work is supported by Fund for Improvement of Science and Technology (FIST) program\, DST\, India\, No.SR/FST/ETII-063/2015 (C) and (G) under the project “Smart Energy Systems Infrastructure – Hybrid Test Bed”.
URL:https://ee.iisc.ac.in/event/thesis-defense-of-tanmay-mishra/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230220T213000
DTEND;TZID=Asia/Kolkata:20230221T003000
DTSTAMP:20260404T012223
CREATED:20230219T225005Z
LAST-MODIFIED:20230219T225107Z
UID:240445-1676928600-1676939400@ee.iisc.ac.in
SUMMARY:An Introduction to Neuromorphic Computing with Intel Loihi
DESCRIPTION:Speaker: Ashish Rao Mangalore\, Doctoral resident at Intel Labs\, Munich\, Germany\nAbstract:\n\nNeuromorphic computing is a new paradigm of computing inspired by the organization and functioning of neurons in the mammalian brain. The architectural features derived from this inspiration result in orders of gain in the time and energy to solution for various classes of problems. Over the years\, there have been neuromorphic platforms of different types\, e.g.\, IBM TrueNorth\, SpiNNaker\, DYNAPs\, and BrainChip Akida to name a few. In this talk\, we shall focus on the state-of-the-art digital CMOS-based neuromorphic research platform\, Loihi\, developed by Intel Corporation. We shall then go through the basic operating principles of Loihi\, problems that Loihi is best suited for\, and the current main algorithmic research verticals being pursued by the neuromorphic research community. After this\, there shall be a special emphasis on mathematical optimization on Loihi\, one of the most promising and viable applications on Loihi. The talk will end with pointers on how groups can get involved to address open problems and contribute to neuromorphic research in general. \n\nBiography of the speaker:\n\nAshish Rao Mangalore currently works as a doctoral resident at Intel Labs\, Munich\, Germany under the supervision of Prof. Alin Albu-Schäffer at the German Aerospace Center/DLR & TU Munich. His main research focus lies in the development & implementation of control algorithms for robotics and mathematical optimization problems on neuromorphic computers\, specifically\, Loihi. During a prior research stint at the Indian Institute of Science (IISc)\, Bengaluru\, he conducted research on 3-D reconstruction techniques with neuromorphic cameras. He obtained his masters in Neuroengineering from the Technical University of Munich (TUM) and bachelors in Electrical & Electronics Engineering from R.V. College of Engineering (RVCE)\, Bengaluru.
URL:https://ee.iisc.ac.in/event/an-introduction-to-neuromorphic-computing-with-intel-loihi/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230220T153000
DTEND;TZID=Asia/Kolkata:20230220T183000
DTSTAMP:20260404T012223
CREATED:20230213T034941Z
LAST-MODIFIED:20230213T034941Z
UID:240423-1676907000-1676917800@ee.iisc.ac.in
SUMMARY:PhD Oral Defense\, of Mr. Bidhan Biswas
DESCRIPTION:Title of the thesis: Short Circuit and Open Circuit Natural Frequencies of 3-Φ Transformers. \nResearch Supervisor: Prof. L. Satish \nMeeting link : Click here to join the meeting \nAbstract \nFrequency Response Analysis (FRA) method is perhaps the most sensitive tool that can detect even the slightest of winding/core movements. High sensitivity\, non-invasiveness\, non-destructiveness\, and on-site capability are some of its salient features – making it an ideal monitoring and detection tool. The existence of Standards (IEEE\, IEC\, and CIGRE) is ample testimony of its global acceptance and superior detection capabilities. The principle of detection is based on observance of a deviation between two measured FRAs which implies a possible fault. Naturally\, the next logical step is to analyse these deviations to determine the type of fault\, estimate the extent of damage and its severity\, and as a bonus\, predict its location\, if possible. However\, even after three decades of existence\, arriving at these inferences  is still at the research level. Even though there is a consensus among all the standards on FRA test/measurement procedures\, best-suited terminal connections\, cable layout\, grounding practices\, etc.\, they remain largely silent regarding interpretation and diagnostics. \nA detailed analysis of literature compiled in Chapter 1 reveals that perhaps lack of a mathematical foundation might be one reason for the present plight of FRA. So\, developing a generic mathematical-based approach for interpretation and location of  incipient mechanical winding damages in actual 3-Φ transformer windings\, using measured FRA\, is imperative. Development of a such generic method necessitates derivation of closed-form expressions which can provide a direct link between measured FRA quantities to the electrical parameters of the winding. For assessing damage severity\, the challenge is to identify a quantity which is not only extractable from measured FRA\, but also be sensitive\, monotonic\, and traceable to the fault. Driven by this philosophy this thesis aims to address the following – \n\nPropose a unified and general approach to derive closed-form analytical expressions (for each multiphase winding) to link the measured open and short circuit natural frequencies to electrical parameters of the winding\, and valid for any condition of the neutral\nDefine a quantity calculable from the measured FRA’s peak/trough frequencies which is physically related to mechanical damage in the winding\, and capable of yielding some physical insight about damage\nDevelop novel methods using the derived analytical expressions to identify an incipient\, discrete\, and localized axial and/or radial displacement in any multiphase winding\, and applicable for any condition of the neutral\n\nIn the second chapter\, a generic and unified analytical method is developed (applicable to any 1-Φ or 3-Φ winding) starting from the basic mutually coupled lossless ladder network model to derive equations which relate the harmonic sum of squares of short circuit natural frequencies (SCNF) and open circuit natural frequencies (OCNF) to the elemental winding inductances and capacitances. Complete details of the derivation are discussed\, and all the derived formulae were cross verified by extensive numerical circuit simulations. \nEach one of these derived expressions has a strikingly similar structure and possesses a unique property viz.\, the contribution of series capacitances and ground capacitances are decoupled. This important property paves way for estimating a physical quantity that is directly responsible for the winding resonances\, viz.\, the effective air-core inductance (Leff). This estimation requires multiple FRA measurements. Chapter 3 presents complete details of the concept\, its derivation\, measurements\, and experimental results for all 1-Φ and 3-Φ windings. \nLoss of clamping pressure in a winding is not directly identifiable by any means\, other than an FRA measurement. But\, this damage cannot be judged by merely comparing two FRAs. So\, a clamping pressure measurement experiment was carried out on a single isolated winding to ascertain the sensitivity and monotonicity afforded by the quantity\, Leff\, to a change in clamping pressure. Driven by the promising results\, author proceeds to build a method based on Leff to find the location of a discrete and localized axial displacement (AD) in any 3-Φ winding configuration. Details of this method\, experimental results\, and measurement steps are presented in Chapter 4. \nProceeding further\, Chapter 5 discusses concept of a new method\,  measurement steps and experimental results to identify presence of a Radial Displacement (RD) in a 3-Φ star winding with neutral-open\, as well as\, in a delta connected winding. Driven by success\, the concept was extended to identify the simultaneous occurrence of a discrete and localized AD and RD in one phase of a 3-Φ star winding\, with neutral-open. Preliminary experimental results proved the method can successfully identify faulted phases that contained AD and RD. \nAll experiments reported in the thesis were carried out on transformer windings rated at 33 kV\, 3.5 MVA. The results are encouraging and the author believes that true potential of the proposed methods can be judged when implemented on actual transformers. \nIn summary\, this thesis presents\, perhaps for the first time\, a mathematical basis for identifying and diagnosing axial and radial displacements in 1-Φ and 3-Φ windings using the peak/trough frequency data from the measured FRA. The author believes that this is a small step forward in advancing FRA as a diagnostic tool. \nALL ARE INVITED
URL:https://ee.iisc.ac.in/event/phd-oral-defense-of-mr-bidhan-biswas/
LOCATION:HV seminar Hall
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230217T213000
DTEND;TZID=Asia/Kolkata:20230217T223000
DTSTAMP:20260404T012223
CREATED:20230213T033242Z
LAST-MODIFIED:20230217T055545Z
UID:240420-1676669400-1676673000@ee.iisc.ac.in
SUMMARY:EE Faculty Colloquium on Learning from unreliable data
DESCRIPTION:Speaker: Prof. P.S. Sastry\, Dept of Electrical Engineering\, Indian Institute of Science \nAbstract: \nSupervised learning of classifiers is widely used in many applications of AI/ML. The deep networks used in such applications today need a large training set. Creating a labelled data set where one can have high confidence in the labels is both expensive and time consuming. Data sets created through crowd sourcing or automatic labelling methods normally have many random labelling errors. There is considerable amount of empirical evidence to show that standard algorithms are likely to do poorly when there is significant amount of label noise in the data. Hence it is interesting to ask whether one can design classifier learning algorithms that are robust to different types of random labelling errors (in the training data). Over the years this problem has been investigated by many researchers and many interesting ideas and algorithms for such robust learning are proposed. In this talk we present an overview of the problem of learning with noisily labelled training set and review some of the approaches proposed for tackling the problem. We concentrate mainly on risk minimization schemes. We discuss what are called symmetric loss functions and their role in robust risk minimization. We will also briefly discuss approaches based on sample selection and weighted risk minimization and present a sample selection algorithm based on batch statistics. The discussion would be biased towards some work done in our lab.Speaker’s Bio:P.S. Sastry obtained BSc in Physics from IIT\, Kharagpur\, and BE from ECE dept and PhD from EE dept at IISc. He has been a faculty member of dept EE\, IISc\, for more than 35 years now. His research interests include Pattern Recognition\, Machine Learning\, Data Mining\, and Computational Neuroscience.
URL:https://ee.iisc.ac.in/event/learning-from-unreliable-data/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230215T223000
DTEND;TZID=Asia/Kolkata:20230215T233000
DTSTAMP:20260404T012223
CREATED:20230214T015525Z
LAST-MODIFIED:20230214T015525Z
UID:240425-1676500200-1676503800@ee.iisc.ac.in
SUMMARY:Towards optimal design of lithium-ion batteries through physics-based modelling by Dr. Krishnakumar Gopalakrishnan
DESCRIPTION:                                                                                                                             Abstract \nFor online participants: Meeting Link  \n\nIncreased driving range and enhanced fast charging capabilities are acknowledged as the immediate goals of transport electrification. However\, these two objectives are at loggerheads with each other\, since they place demands on improving two contrasting aspects of vehicular pouch-cell design\, viz. their energy and power densities. By varying the number of layers versus the volume of active electrode material\, bespoke pouch-cell designs targeting either of these goals can be obtained. Attempting this design trade-off through iterative empirical testing of layer choices is expensive and often leads to sub-optimal designs. This talk presents the author’s research towards developing a computational framework that employs a model-based methodology for determining the optimal number of electrochemical layers. The modelling objective is to maximise the usable energy whilst satisfying specific acceleration and fast charging targets.\n\nCurrently\, the model developed thus far is able to handle the critical need to avoid lithium plating during fast charging and accounts for a range of thermal conditions. The modelling framework also takes into account the electrochemical and kinetic phenomena at the micro-scale using a hybrid Finite Element (FE)-spectral scheme\, whilst propagating the results upwards to higher length scales for cell-level system design. Drawing upon inferences from his recent research into Hierarchical Multi-Scale Modelling (HMM) of composite materials\, the author shall conclude the talk by presenting preliminary results from his hypothesis that coupling the micro-scale FE quadrature points to nano-scale phenomena shall\, for the first time\, help to quantify the influence of electrode cracking on cell capacity degradation.\n\n\nSpeaker’s bio:\n\n\n\nDr Krishnakumar Gopalakrishnan is a Senior Research Software Engineer at the Dept of Advanced Research Computing (ARC)\, University College London (UCL) in the UK where he works on high performance scientific computing (HPC) applications across a range of computational modelling research projects. Prior to this\, he held a 2-year post doctoral research fellowship in scientific computing at the Centre for Computational Science (CCS) at University College London (UCL)\, UK\, and has served as a visiting researcher at the University of Konstanz\, and Rutherford Appleton Laboratories (RAL)\, UK.He holds a BTech degree in Electrical and Electronics Engineering from College of Engineering\, Thiruvananthapuram\, an MS degree in Electrical Engineering (power electronics systems & control) from the Center for Power Electronics Systems (CPES) labs at Virginia Tech. Later\, he won a US Dept of Energy GATE fellowship to complete a graduate certificate program in electric drivetrain automation. Dr Gopalakrishnan received his PhD degree in Mechanical Engineering (mathematical modelling of lithium ion batteries) from Imperial College London. He was formerly employed at ABB Innovation Labs (Bangalore\, India) and ABB Corporate Research Center (Baden-Dättwil\, Switzerland). He has also served as a power management algorithms and systems engineer at Qualcomm Inc. (San Diego\, USA) where he successfully filed corporate patents on novel Battery Management Systems (BMS) designs. He was awarded the President’s PhD Scholarship at Imperial College London and is a Mathworks Certified Matlab Associate.\n\nDr Gopalakrishnan has over a decade of teaching experience at various levels. At UCL\, he currently teaches the University’s scientific computing with C++ course and is leading the course development effort and teaching plan for UCL ARC’s first Massively Open Online Course (MOOC) on the FutureLearn platform. He has also had the privelege of teaching Imperial College London’s first MOOC on Mathematics Essentials (for business majors) hosted on the EdX platform. He has also served as a teaching fellow at Imperial College London’s Computational Methods hub\, wherein he was the lead instructor for several scientific computing courses taught to a campus-wide audience.\n\n\nDr Gopalakrishnan has published several well-cited research articles in peer-reviewed journals (including in Nature Computational Science) and technical whitepapers\, and has presented at UK and international conferences. His research software engineering interests include heterogeneous and GPU computing\, parallel and threaded programming\, linear algebra libraries\, low-latency network communications\, and Unix systems administration. His scientific research interests include computational modelling of dynamic systems\, power electronics and control\, energy storage\, non-linear optimisation\, feedback control\, signal processing\, numerical methods and state estimation.
URL:https://ee.iisc.ac.in/event/towards-optimal-design-of-lithium-ion-batteries-through-physics-based-modelling-by-dr-krishnakumar-gopalakrishnan/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230125T163000
DTEND;TZID=Asia/Kolkata:20230125T173000
DTSTAMP:20260404T012223
CREATED:20230125T032338Z
LAST-MODIFIED:20230125T032338Z
UID:240262-1674664200-1674667800@ee.iisc.ac.in
SUMMARY:PhD Thesis Defense of Dhruv Jawali
DESCRIPTION:Advisors: Prof. Chandra Sekhar Seelamantula (EE) & Prof. Supratim Ray (CNS)\n\nExaminer: Prof. Vikram M. Gadre (EE)\, IIT Bombay\nTitle of the thesis: Learning Filters\, Filterbanks\, Wavelets\, and Multiscale Representations\n\nDate & Time: January 25\, 2023; 11:00 AM onward (Coffee will be served during the defense)\nVenue: Multimedia Classroom (MMCR)\, Department of Electrical Engineering\, IISc\nAbstract:\n\nThe problem of filter design is ubiquitous. Frequency selective filters are used in speech/audio processing\, image analysis\, convolutional neural networks for tasks such as denoising\, deblurring/deconvolution\, enhancement\, compression\, etc. While traditional filter design methods use a structured optimization formulation\, the advent of deep learning techniques and associated tools and toolkits enables the learning of filters through data-driven optimization. In this thesis\, we consider the filter design problem in a learning setting in both data-dependent and data-independent flavors. Data-dependent filters have properties governed by a downstream task\, for instance\, filters in a convolutional dictionary used for the task of image denoising. On the contrary\, data-independent filters have constraints imposed on their frequency responses\, such as lowpass\, having diamond-shaped support\, satisfying perfect reconstruction property\, ability to generate wavelet functions\, etc.\nThe contributions of this thesis are four-fold: (i) the formulation of filter\, filterbank\, and wavelet design as regression problems\, allowing them to be designed in a learning framework; (ii) the design of contourlet-based scattering networks for image classification; (iii) the design of a deep unfolded network using composite regularization techniques for solving inverse problems in image processing; and (iv) a multiscale dictionary learning algorithm that learns one or more multiscale generator kernels to parsimoniously explain certain neural recordings.We begin by developing learning approaches for designing filters having data-independent specifications\, for instance\, filters with a specified frequency response\, including an ideal filter. The problem of designing such filters is formulated as a regression problem\, using a training set comprising cosine signals with frequencies sampled uniformly at random. The filters are optimized using the mean-squared error loss\, and generalization bounds are provided. We demonstrate the applicability of our approach for filters such as lowpass\, bandpass\, and highpass in 1-D\, and diamond\, fan and checkerboard support filters in 2-D. We then show how the methodology extends easily for designing 1-D and 2-D cosine modulated filterbanks.\nSecond\, we consider the problems of 1-D filterbank and wavelet design through learning. Wavelets have proven to be highly successful in several signal and image processing applications. Wavelet design has been an active field of research for over two decades\, with the problem often being approached analytically. We draw a parallel between convolutional autoencoders and wavelet multiresolution approximation and show how the learning angle provides a coherent computational framework for solving the design problem. We design data-independent wavelets by interpreting the corresponding perfect reconstruction filterbanks as autoencoders (what we refer to as “filterbank autoencoders”)\, which precludes the need for customized datasets. In fact\, we show that it is possible to design them efficiently using high-dimensional Gaussian vectors as training data. Generalization bounds show that a near-zero training loss implies that the learnt filters satisfy the perfect reconstruction property with a very high probability. We show that desirable properties of a wavelet such as orthogonality\, compact support\, smoothness\, symmetry\, and vanishing moments can all be incorporated into the proposed framework by means of architectural constraints or by introducing suitable regularization functionals to the MSE cost. Notably\, our approach not only recovers the well-known Daubechies family of orthogonal wavelets and the Cohen-Daubechies-Feauveau (CDF) family of symmetric biorthogonal wavelets\, which are used in JPEG-2000 compression\, but also learns new wavelets outside these families.\nThird\, we extend the ideas used for 1-D filterbank and wavelet learning to 2-D filterbank and wavelet design. A variety of efficient representations of natural images\, such as wavelets and contourlets can be formulated as corresponding filterbank design problems. The design constraints on the continuous-domain wavelets have corresponding filter-domain manifestations. While most learning problems require specialized datasets\, we employ 2-D random Gaussian matrices as training data and optimize filter coefficients considering the MSE loss. Design specifications such as orthogonality of the filterbank\, perfect reconstruction property\, symmetry\, and vanishing moments are enforced through an appropriate parameterization of the convolutional units. We demonstrate several examples of learning biorthogonal and orthogonal filterbanks and wavelets having a specified number of vanishing moments\, both point vanishing moments and directional vanishing moments\, and symmetry constraints. Sparse recovery via composite regularization is an interesting approach proposed recently in the literature. One could design non-convex regularizers through a convex combination of sparsity-promoting penalties with known proximal operators. We develop a new algorithm\, namely\, convolutional proximal-averaged thresholding algorithm (C-PATA) for {\it composite-regularized} convolutional sparse coding (CR-CSC) based on the recently proposed idea of proximal averaging. We develop an autoencoder structure based on the deep-unfolding of C-PATA iterations into neural network layers\, which results in the composite-regularized neural network (CoRNet) architecture. The convolutional learned iterative soft-thresholding algorithm becomes a special case of CoRNet. We demonstrate the efficacy of CoRNet considering applications to image denoising and inpainting\, and compare the performance with state-of-the-art techniques such as BM3D\, convolutional LISTA\, and fast and flexible convolutional sparse coding (FFCSC).The data-independent filter design technique is employed to learn a contourlet transform used within a hybrid scattering network. Hybrid scattering networks are convolutional neural networks (CNNs) where the first few layers implement a fixed windowed scattering transform\, while the rest of the network is learned. Scattering networks outperform state-of-the-art deep learning models for limited-data classification tasks although the performance gains are not much for large datasets. The 2-D Morlet filterbank used in Mallat’s scattering network is replaced by a contourlet filterbank\, which provides sparser representations and better frequency-domain directional separation. The contourlet transform comprises a multiresolution pyramidal filterbank cascaded with directional filters. We construct directional filters using diamond-shaped quincunx filterbanks and consider two pyramidal filter variants — square-shaped\, and filters with radially isotropic frequency domain support. The performance of all variants is evaluated for natural image classification tasks on CIFAR-10 and ImageNet datasets. We show that the radial contourlet variant achieves competitive performance compared with the Morlet scattering transform on large-dataset classification tasks while performing better for the limited-dataset scenario.We then switch over to the problem of learning data-dependent filters for sparse recovery by employing a combination of sparsity promoting regularizers. Sparse recovery via such composite regularization approaches is an interesting framework proposed recently in the literature. One could design non-convex regularizers through a convex combination of sparsity-promoting penalties with known proximal operators. We developed a new algorithm\, namely\, convolutional proximal-averaged thresholding algorithm (C-PATA) for composite-regularized convolutional sparse coding (CR-CSC) based on proximal averaging. We develop an autoencoder structure based on the deep-unfolding of C-PATA iterations into neural network layers\, which results in the composite-regularized neural network (CoRNet) architecture. The convolutional learned iterative soft-thresholding algorithm becomes a special case of CoRNet. We demonstrate the efficacy of CoRNet considering applications to image denoising and inpainting and compare the performance with state-of-the-art techniques such as BM3D\, convolutional LISTA\, and fast and flexible convolutional sparse coding (FFCSC).Finally\, we conclude by developing a data-dependent method to learn filters generating a multiscale convolutional dictionary. First\, the multiscale convolutional dictionary learning (MCDL) algorithm is proposed to extract a representative waveform shape from a given dataset. The proposed algorithm is based on the popularly used convolutional dictionary learning formulation with a crucial difference — we assume that the learned atoms are scaled versions of a single generator kernel. We evaluate kernel recovery for synthetic data under noiseless and noisy data conditions. A smoothness regularizer on the learned atom is used to aid better kernel recovery under noisy conditions. Kernel recovery is shown to be robust to model choices of scales and the assumed support size of the kernel without any restrictive assumptions. The proposed approach is applied to visualizing the typical patterns present within human electrocorticogram (ECoG) measurements. The validation is carried out using publicly available ECoG data recorded from a single Parkinson’s disease patient.This thesis thus presents a cogent framework for learning filters\, filterbanks\, wavelets\, convolutional and multiscale dictionaries.\nBiography of the candidate: Dhruv Jawali received the Bachelor of Technology (B. Tech) degree from the Department of Computer Science and Engineering\, National Institute of Technology Goa\, India\, in 2014. He worked as a software developer at the Samsung Research Institute\, Bangalore during 2014-2015. He enrolled into the PhD program at the IISc Mathematics Initiative (IMI) Department\, Indian Institute of Science (IISc) in August 2015\, and has been working at the Spectrum Lab\, Department of Electrical Engineering ever since. His research interests include wavelet theory\, deep neural networks\, and sparse signal processing. He is currently employed as an instructor at Scaler Academy specializing in Data Science and Machine Learning.\n\nAll are invited.
URL:https://ee.iisc.ac.in/event/phd-thesis-defense-of-dhruv-jawali/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230124T163000
DTEND;TZID=Asia/Kolkata:20230124T173000
DTSTAMP:20260404T012223
CREATED:20230125T033041Z
LAST-MODIFIED:20230125T033041Z
UID:240264-1674577800-1674581400@ee.iisc.ac.in
SUMMARY:Ph.D thesis Defense of Mr.Sounak Nandi
DESCRIPTION:Title of Thesis: Experimental and Theoretical Investigations on High Voltage Polymeric Insulators.  \nResearch Supervisor:  Subba Reddy B  \nDate and Time: Tuesday 24th Jan 2023\, 11am  \nVenue: ON Line: Meeting link:  \nAbstract  \nHigh Voltage Ceramic and glass Insulators have been widely used by various transmission and distribution utilities for several decades across the globe. Recently composite or silicone rubber insulators have evolved and are now replacing ceramic/glass insulators due to their improved advantages; however\, these Insulators suffer from degradation over a period of service.   \nThe Primary objective of the investigation relates to the study of silicon rubber/polymer insulators under various climatic conditions. Exhaustive experimental studies were conducted to understand the degradation of insulators under different climatic conditions which prevail in the Country.   \nStudies on polymer insulators under sub-zero and under extremely high-temperature conditions were attempted experimentally to evaluate their performance. During experimentation\, the leakage current was continuously monitored. Later\, material analysis\, which is a very important aspect and essential to correlate with the morphological changes of the insulator surface\, was examined. The experimental investigations demonstrate that there is a need to conduct multi-stress experimentation under specific climatic conditions before the Insulators are installed in the field.   \nThe next portion of the thesis work deals with the failure mechanism of a Fibre Reinforced Plastic (FRP) Rod. Some portion of the work deals with mathematical analysis being extended to condition monitoring of dielectric surfaces and understanding the performance of FRP rods under high AC voltages. Further\, experimental investigations are performed on FRP Rods to analyze the behaviour witnessed\, as the field failures reported on Silicon rubber Insulators\, interesting results are reported.   \nCondition monitoring of dielectric surfaces is very important; hence it was felt necessary to analyze the field performance of transmission/distribution composite Insulators. To understand further\, a mathematical analysis based on Chaos has been evaluated for leakage current data and quantization of comparative degradation for a dielectric surface is presented. Later\, Empirical Mode Decomposition is also used for understanding leakage current and implied degradation under minimal data conditions.  \nSubsequently\, the Surface electric field of insulators exposed to HVDC is studied considering the temporal boundary conditions which may arise due to the capacitive-resistive transients. Some experimental investigations are also conducted to compare the simulated results.  \n\nThe last portion of the thesis emphases on the study of bulk conductivity of polymer material. The Electric Field dependence of conductivity on the application of voltage and subsequent space charge distribution is attempted.  In short\, the thesis work reports some new findings on the experimental\, simulation and theoretical studies pertaining to the high voltage polymeric insulators used for EHV/UHV Transmission.  \n\nAll are welcome
URL:https://ee.iisc.ac.in/event/ph-d-thesis-defense-of-mr-sounak-nandi/
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230120T213000
DTEND;TZID=Asia/Kolkata:20230120T223000
DTSTAMP:20260404T012223
CREATED:20230117T002035Z
LAST-MODIFIED:20230117T002448Z
UID:240253-1674250200-1674253800@ee.iisc.ac.in
SUMMARY:EE Faculty Colloquium by Prof. Kaushik Basu
DESCRIPTION:Venue: MMCR\, EE \nTime: 4pm\, 20 January 2023 \nAbstract:Silicon Carbide MOSFETs (SiC MOSFETs) fall into wide band gap (WBG) power devices. These devices are commercially available in the voltage range of 600-3300V and compete with the state-of-the-art Si-insulated gate bipolar junction transistors (IGBTs). Superior material properties  of SiC MOSFET lead to smaller die sizes. This results in faster switching transients and lower switching loss. However\, it excites device and circuit parasitic that may lead to prolonged oscillation\, high device stress\, spurious turn-on and EMI-related issues. So\, the benefit of using SiC MOSFET as a power device comes with numerous design challenges resulting in slow commercial adaptation. It is predicted that the overall market share of WBG devices (SiC and GaN together) will be roughly 10% of the total market for power semiconductors by 2025. To overcome the design challenges and fully utilise the benefits of fast-switching SiC MOSFETs\, a better understanding of switching dynamics is essential. However\, the switching dynamics of SiC MOSFET are different compared to its Si counterpart due to the highly non-linear device characteristics and participation of circuit parasitic in the process. In this talk\, we will discuss our recent work on developing an analytical model of the switching dynamics for hard and soft transitions of SiC MOSFET by simplifying the complex non-linear dynamics predicted by the behavioural model. The developed model\, given the device-related parameters extracted from the data sheet\, estimated or measured circuit parasitic\, can predict lost switching energy\, rate of change of device voltage etc.\, necessary for a successful power converter design through computation with sufficient accuracy. Based on this model a Python based interactive software tool has been developed. The results of this work are applied to two WBG-based advanced power converter development: A 3kW onboard charger for 2 Wheelers and a 200kW SiC-based inverter for high-bandwidth power amplifiers.Speaker’s Bio:Kaushik Basu received the BE. Degree from the Bengal Engineering and Science University\, Shibpore\, India\, in 2003\, the M.Sc. degree in electrical engineering from the Indian Institute of Science (IISc)\, Bangalore\, India\, in 2005\, and the PhD degree in electrical engineering from the University of Minnesota\, Minneapolis\, in 2012\, respectively. He was a Design Engineer with Cold Watt India in 2006 and an Electronics and Control Engineer with Dynapower Corporation USA from 2013-to 15. He is an Associate Professor in the Department of Electrical Engineering at the IISc. He served as the Technical Program Committee Vice-Chair of IEEE ECCE 2019 and 2022. In 2019\, he received the Prof. Priti Shankar Teaching Award from IISc. As a co-author\, he received the Second Best Prize Paper Award from IEEE Transactions on Transportation Electrification in 2021.  He is IEEE senior member and is the founding chair of both IEEE PELS and IES Bangalore Chapter. He is an Associate Editor of IEEE Transactions on Power Electronics\, IEEE Transactions on Industrial Electronics\, and Springer Journal of Power Electronics. His research interests include most aspects of Power Electronic converter design from a few kW to a few MW for applications ranging from space\, grid integration of renewables and storage to fast charging of electric vehicles.
URL:https://ee.iisc.ac.in/event/ee-faculty-colloquium-by-prof-kaushik-basu/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230112T203000
DTEND;TZID=Asia/Kolkata:20230112T213000
DTSTAMP:20260404T012223
CREATED:20230109T051231Z
LAST-MODIFIED:20230109T051231Z
UID:240242-1673555400-1673559000@ee.iisc.ac.in
SUMMARY:Thesis Colloquium of Sayan Paul
DESCRIPTION:Thesis Title: Pulse Width Modulation Techniques of Inverter Fed Split-Phase Machine Drive in Linear and Overmodulation Regions \nDegree registered: PhD \nGuide: Prof. Kaushik Basu \nDate and Time: 12th January 2023\, 03:00 PM \nPlace: MMCR EE\, \nMeeting Link: Teams Meeting Link \nMulti-phase machines (MPMs) have more than three windings in their stator\, rotor\, or both. With the broader adoption of power-electronic converters for efficient driving of the machines\, MPMs are gaining attention in different applications due to their certain advantages over three-phase machines. One such advantage is higher fault tolerance due to higher phase redundancy\, which makes it suitable for safety-critical applications like electric vehicles (EVs)\, ship propulsions\, electric aircraft\, etc. Another advantage is that MPMs allow power splitting across multiple phases. Hence\, the power rating per phase drive unit becomes low\, making it suitable for high-power applications like railway traction\, pumps\, compressors\, etc. Recent literature also proposes using the same multi-phase converter fed MPM\, otherwise used for propulsion\, as an onboard battery charger; it substantially reduces space\, weight\, and cost. During charging mode\, the leakage inductance of the machine provides the required inductance for the grid connection\, and MPM’s higher degrees of freedom are used to lock the rotor electronically. An asymmetrical six-phase machine (ASPM) or split-phase machine is one such MPMs and is very common in EVs. This thesis aims to devise the pulse-width modulation (PWM) techniques of a two-level six-phase inverter fed ASPM to improve the overall drive efficiency. \nASPM has two sets of balanced three-phase windings\, which are spatially shifted by 30 degrees (electrical angle). In one of the popular configurations\, the two three-phase winding sets are connected in star fashion with two isolated neutral points. This machine is conventionally analyzed in two two-dimensional (2D) orthogonal subspaces. One of these subspaces is associated with electromagnetic energy transfer and torque production. The other subspace doesn’t transfer energy through the air gap and the equivalent circuit in this plane\, consisting of winding resistance and leakage inductance\, provides a low impedance. Therefore\, excitation of this non-energy-transferring subspace causes a large current and associated copper loss. Any PWM technique of ASPM aims to synthesize the desired voltages in the energy-transferring plane and minimize the applied voltage in the non-energy-transferring subspace. \nLinear modulation techniques (LMTs) of ASPM apply zero average voltage in the non-energy-transferring subspace and synthesize the desired voltages in the energy-transferring plane on an average over a switching cycle. It is expected that these LMTs should avoid more than two switching transitions of an inverter leg within a carrier period to limit the instantaneous switching loss. Through an innovative approach\, our work finds a way to account for all possible infinitely many LMTs that follow the rule of at most two transitions per leg. But each of them results in a different current ripple performance. Ripple current is inevitable in PWM converters and should be minimized through modulation to reduce the associated copper loss. The total ripple current RMS of ASPM is contributed by both energy-transferring and non-transferring planes. One machine parameter also impacts this performance: the ratio of high-frequency inductances in these two subspaces. For all reference voltage vectors and the whole feasible range of the machine parameter\, our work finds the techniques with minimum current ripple (RMS) among the above infinite possible LMTs through numerical optimization. A hybrid PWM strategy is proposed with these optimal techniques\, which outperforms all existing techniques regarding current ripple performance. \nOvermodulation (OVM) techniques of ASPM attain higher voltage gain in energy-transferring subspace than LMTs by applying non-zero average voltage in the non-energy transferring subspace. This operation doesn’t cause any torque ripple\, but the applied voltage in non-energy transferring subspace should be minimised to reduce unwanted current and associated loss. The existing OVM technique in the literature minimizes this average voltage from the space-vector perspective with a pre-defined set of four active vectors. To find the best technique\, one needs to perform the above minimization problem with all possible sets of active vectors\, which can give higher voltage gain. So\, this requires the evaluation of a large number of cases. In this thesis\, we have formulated the above minimization problem in terms of average voltage vectors of two three-phase inverters\, where active vectors need not be specified beforehand. Thus\, the analysis is more general. Following the above analysis\, eight switching sequences in one part and two in another part of the OVM region are derived\, which attain the minimum average voltage injection in the non-energy transferring subspace. \nAlthough the above OVM sequences apply the same average voltages in the two subspaces\, they have different high-frequency ripple currents due to different switching strategies. The current ripple study of the OVM techniques of ASPM is missing in the literature. Hence\, one of our works in the thesis studies the current ripple performances of the above optimal PWM sequences in the OVM region\, which apply minimum average voltage in the non-energy-transferring subspace. We find the sequence with the best switching current ripple performance for a given reference vector in the OVM region and the machine parameter. After that\, a PWM technique is proposed\, which substantially improves the high-frequency current ripple performance (RMS) compared to two existing OVM techniques for a given machine parameter value. \nFinally\, simple carrier-comparison-based implementation methods of the proposed LMTs and OVM sequences are found. The six-phase inverter is split into two three-phase inverters\, and the proposed strategy implements the PWM sequences per three-phase inverter basis. In carrier-based implementations\, the duty signal of the top switch of an inverter leg is compared with a triangular carrier. The bottom switch’s gating pulse complements the top switch’s pulse with a fixed dead time. The duty signal of the top switch of any leg has two components- a modulation signal and a common-mode signal. Two 180-degree phase-shifted carrier signals are required to implement the proposed sequences. The energy-transferring plane of ASPM is divided into twenty-four equivalent sectors; the carrier signals and the expressions of modulation and common-mode signals differ from one sector to another. Henceforth\, a sector-independent algorithm is proposed in this thesis to derive these duty signals that substantially reduce the computational burden. \nThe proposed techniques are validated through simulation in MATLAB/Simulink and experiments on a hardware prototype at a power level of 4 kW.
URL:https://ee.iisc.ac.in/event/thesis-colloquium-of-sayan-paul/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230111T223000
DTEND;TZID=Asia/Kolkata:20230111T233000
DTSTAMP:20260404T012223
CREATED:20230110T223726Z
LAST-MODIFIED:20230110T223914Z
UID:240244-1673476200-1673479800@ee.iisc.ac.in
SUMMARY:Lecture by Prof. Anubha Gupta
DESCRIPTION:Department of Electrical Engineering\, Indian Institute of Science  \n\n\nand  \n\n\nIEEE Signal Processing Society\, Bangalore Chapter  \n\n\n  \n\n\ncordially invite you to a lecture on  \n\n\nProper Definition of Dirichlet Conditions and Convergence of Fourier Representations  \n\n\n By  \n\n\n Prof. Anubha Gupta  \n\n\nIndraprastha Institute of Information Technology -Delhi  \n\n\n Date and time: January 11\, 2023\, 5 PM  \n\n\n Venue: Multimedia Classroom\, Department of Electrical Engineering (EE)\, IISc.  \n\n\n Coffee will be served during the talk.  \n\n\n Abstract:  Fourier theory is the backbone of Signal Processing (SP) and Communication Engineering. It has been widely used in almost all branches of science and engineering in numerous applications since its inception. However\, Fourier representations such as Fourier series (FS) and Fourier transform (FT) may not exist for some signals that fail to fulfil a predefined set of Dirichlet conditions (DCs). We note a subtle gap in explaining these conditions as available in the popular SP literature. For example\, the original DCs require a signal to have bounded variations over one time period for the convergence of FS\, where there can be at most countably infinite number of maxima and minima\, and at most countably infinite number of discontinuities of finite magnitude. However\, a large body of the literature replaces this statement with the requirements of a finite number of maxima and minima over one time period\, and a finite number of finite discontinuities over one time period. Due to the latter\, some signals fulfilling the original DCs are incorrectly perceived as not having convergent FS representation. A similar problem holds in the description of DCs for the FT. This talk is based on our recent lecture notes published in IEEE Signal Processing Magazine (Sep 2022 issue)\, wherein we provide the required clarifications and a lucid but precise description and explanation on the DCs along with a lot of suitable examples.  \n\n\n Brief Bio:  \n\n\n \n\n\nAnubha Gupta (anubha@iiitd.ac.in) received her B.Tech and M.Tech from Delhi University\, India in 1991 and 1997 in Electronics and Communication Engineering. She received her PhD. from Indian Institute of Technology (IIT)\, Delhi\, India in 2006 in Electrical Engineering. She did her second master’s as a full-time student from the University of Maryland\, College Park\, USA from 2008-2010 in Education. She worked as Assistant Director with the Ministry of Information and Broadcasting\, Govt. of India (through Indian Engineering Services) from 1993 to 1999 and\, as faculty at NSUT-Delhi (2000-2008) and IIIT-Hyderabad (2011-2013)\, India. Currently\, she is working as a Professor at IIIT-Delhi\, where she served as the Dean\, Academic Affairs from June 2019 to June 2020. She has authored/co-authored more than 100 technical papers in scientific journals and conferences. She received SERB POWER Fellowship\, 2021 from DST. Govt. of India. She has published research papers in both engineering and education. A lot of exciting work is being taken up in her lab: SBILab (Lab: http://sbilab.iiitd.edu.in/index.html \n\n\n\n\n\nSBILab – Indraprastha Institute of Information Technology\, Delhi\nSignal Processing and Biomedical Imaging Lab. Led By Prof. Anubha Gupta of IIIT-Delhi (Started in Jan 2014) SBILab focuses on Signal Processing areas including applications of Wavelet Transforms\, Machine (Deep) Learning\, and Compressed Sensing\, Sparse Reconstruction\, fMRI/EEG/MRI/DTI Signal and Image Processing\, Genomics Signal Processing\, Signal Processing for Communication Engineering\, and …\nsbilab.iiitd.edu.in\n\n\n\n\n\n). Her research interests include applications of machine learning in cancer genomics\, cancer imaging\, biomedical signal and image processing including fMRI\, MRI\, EEG\, ECG signal processing\, and Wavelets in deep learning. Dr. Gupta is a senior member of IEEE Signal Processing Society (SPS) and a member of IEEE Women in Engineering Society. She is a technical committee member of BISP committee of IEEE SPS Society for Jan 2022– Dec 2024.   \n\n\n  \n\n\nHost: Prof. Chandra Sekhar Seelamantula\, EE\, IISc.  \n\n\n  \n\n\nAll are invited. 
URL:https://ee.iisc.ac.in/event/lecture-by-prof-anubha-gupta/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230106T153000
DTEND;TZID=Asia/Kolkata:20230106T163000
DTSTAMP:20260404T012224
CREATED:20221227T011631Z
LAST-MODIFIED:20221227T011659Z
UID:240210-1673019000-1673022600@ee.iisc.ac.in
SUMMARY:Seminar by Prof. Niladri Chakraborty
DESCRIPTION:Title: Emulator-based Microgrid studies vis a vis Some Indian Renewable interconnected Microgrids. \nTime: 10 am 6/1/23 \nVenue: EE MMCR \nAbstract: Mini / Micro Grid in Stand Alone or Grid integrated forms are coming up very fast in the conventional power system. Many a time\, these are renewable sources integrated. Design considerations\, Plant automation\, Remote monitoring and O & M strategies play important roles in their operational exploitation. However\, for economics and systematic\, technically sound energy businesses\, it is prudent to have emulator-based studies done before these systems are commercially realized. Attempts will be made to showcase an emulator-based microgrid available in the Department of Power Engineering\, Jadavpur University\, Kolkata. At the same time\, generalized Design considerations\, Plant automation\, Remote monitoring\, O & M strategies and System studies will be briefly highlighted.  Introduction of different types of renewable integrated Mini / Microgrids encountered during consultancy services or for technical studies available elsewhere in the pan-Indian domain will be made perceptible to the audience. \n Bio: Prof Niladri Chakraborty was born in Kolkata on 27/08/1964. He received his Bachelor’s (1986) and Masters’s Degree (1989) in Electrical Engineering from Jadavpur University\, Kolkata\, India. He was the recipient of the prestigious Commonwealth Scholarship in the United Kingdom and obtained the Diploma of Imperial College and Doctor of Philosophy from the University of London in 1999. He was elected as the youngest Dean of the Faculty of Engineering and Technology at Jadavpur University in 2010. He has served twice as Head of the Department of Power Engineering and as Joint Director of the School of Energy Studies at Jadavpur University. He was often elected to the Executive Council and The Court\, the highest policy-making academic body of Jadavpur University. He has also received Scholarships from the Royal Society (UK)-DST and Abdul Kalam Award\, besides many other awards from numerous academic activities. Dr Chakraborty has served as one of the Lead Scientists in India’s National Communication to United Nations on Climate Change (NATCOM\, India\, UNFCCC) and a Specialized Energy Expert in formulating the Futuristic Energy Action Plan for the Government of West Bengal\, India. He has also completed many research projects obtained from different funding agencies and earned revenue for Jadavpur University as a consultant. \n Prof. Chakraborty’s recent research interests include Energy Economics\, Renewable integrated Microgrid\, Environmental Measurement and Material Modelling. Dr Chakraborty has in his credit to be the author of about 75 referred journal publications and nearly 130 International Conference Publications. Prof. Chakraborty has guided 13 PhDs (4 more are in writing-up status) and 41 Masters of Engineering Thesis.
URL:https://ee.iisc.ac.in/event/seminar-by-prof-niladri-chakraborty/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230102T213000
DTEND;TZID=Asia/Kolkata:20230102T223000
DTSTAMP:20260404T012224
CREATED:20221229T225034Z
LAST-MODIFIED:20221229T225125Z
UID:240213-1672695000-1672698600@ee.iisc.ac.in
SUMMARY:Lecture by Prof. Manoj Saranathan
DESCRIPTION:Department of Electrical Engineering\, Indian Institute of Science\nand\nIEEE Signal Processing Society\, Bangalore Chapter\ncordially invite you to a lecture on \nAdvances in imaging and segmentation of thalamic nuclei with applications \nby \nProf. Manoj Saranathan\, Professor of Radiology at UMass Chan Medical School in Worcester\, Massachusetts \nDate and time: January 2\, 2023\, 4 PM\nVenue: Multimedia Classroom\, Department of Electrical Engineering (EE)\, IISc. \nCoffee will be served at 3.45 PM. \nAbstract: The thalamus is a subcortical deep brain structure increasingly implicated in a number of neurodegenerative and neuropsychiatric conditions. It is subdivided into regions called nuclei which are linked to specific cortical and sensory regions of the brain. However\, thalamic nuclei have largely been ignored in most imaging studies as they are mostly invisible in conventional MRI. In this talk\, I will present our work on MRI methods to improve visualization of thalamic nuclei as well as cutting edge thalamic nuclei segmentation methods. I will then show examples of characterization of atrophy of specific thalamic nuclei in neurodegenerative diseases as well as for cutting edge neurosurgical treatment of epilepsy and essential tremor. \nBiography of the speaker: Manoj Saranathan is an MRI physicist with over twenty-five years of experience in MR physics\, pulse sequence development\, image reconstruction\, and image processing spanning industry and academia. His current research interests are focused on ultra high-resolution imaging and segmentation of deep brain structures like thalamus and hippocampus and the specificity of their involvement in pathology such as alcoholism\, multiple sclerosis\, Alzheimer’s disease\, and essential tremor. Another area of interest is high spatio-temporal resolution dynamic contrast enhanced MRI for quantification of physiologic function and cancer. One of his methods\, DISCO\, is now a product available on all GE MRI scanners since 2017\, and is widely used for prostate and breast imaging worldwide. He has a PhD in Bioengineering from the University of Washington\, Seattle and is currently a Professor of Radiology at UMass Chan Medical School in Worcester\, Massachusetts. \nHosts: Prof. P. S. Sastry and Prof. Chandra Sekhar Seelamantula\, EE\, IISc \nAll are invited.
URL:https://ee.iisc.ac.in/event/lecture-by-prof-manoj-saranathan/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230102T163000
DTEND;TZID=Asia/Kolkata:20230102T173000
DTSTAMP:20260404T012224
CREATED:20221226T032757Z
LAST-MODIFIED:20221226T032848Z
UID:240207-1672677000-1672680600@ee.iisc.ac.in
SUMMARY:Thesis Defence of Mr. Ruturaj Gavaskar
DESCRIPTION:Title: On Plug-and-Play Regularization using Linear Denoisers.\nDegree Registered: PhD\nGuide: Prof Kunal Narayan Chaudhury\nDate: Jan 2\, 2023.\nTime: 11:00 am. \nVenue: Online.\nMS Teams: https://tinyurl.com/bdz95wmw\n(meeting ID: 483 231 041 151; Passcode: QDF8WS) \nAbstract: The problem of inverting a given measurement model comes up in several computational imaging applications. For example\, in CT and MRI\, we are required to reconstruct a high-resolution image from incomplete noisy measurements\, whereas in superresolution and deblurring\, we try to infer the ground truth from low-resolution or blurred images. Traditionally\, this is done by minimizing f + φ\, where f is a data-fidelity (or loss) function that is determined by the acquisition process\, and φ is a regularization (or penalty) function that is based on a subjective prior on the target image. The solution is obtained numerically using iterative algorithms such as ISTA or ADMM. \nWhile several forms of regularization and associated optimization methods have been proposed in the imaging literature over the last few decades\, the use of denoisers (aka denoising priors) for image regularization is a relatively recent phenomenon. This has partly been triggered by advances in image denoising in the last 20 years\, leading to the development of powerful image denoisers such as BM3D and DnCNN. In this thesis\, we look at a recent protocol called Plug-and-Play (PnP) regularization\, where image denoisers are deployed within iterative algorithms for image regularization. PnP consists of replacing the proximal map — an analytical operator at the core of ISTA and ADMM — associated with the regularizer φ with an image denoiser. This is motivated by the intuition that off-the-shelf denoisers such as BM3D and DnCNN offer better image priors than traditional hand-crafted regularizers such as total variation. While PnP does not use an explicit regularizer\, it still makes use of the data-fidelity function f. However\, since the replacement of the proximal map with a denoiser is ad-hoc\, the optimization perspective is lost — it is not clear if the PnP iterations can be interpreted as optimizing some objective function f + φ. Remarkably\, PnP reconstructions are of high quality and competitive with state-of-the-art methods. Following this\, researchers have tried explaining why plugging a denoiser within an inversion algorithm should work in the first place\, why it produces high-quality images\, and whether the final reconstruction is optimal in some sense.\nIn this thesis\, we try to answer such questions\, some of which have been the topic of active research in the imaging community in recent years. Specifically\, we consider the following questions. \n1. Fixed-point convergence: Under what conditions does the sequence of iterates generated by a PnP algorithm converge? Moreover\, are these conditions met by existing real-world denoisers? \n2. Optimality and objective convergence: Can we interpret PnP as an algorithm that minimizes f + φ for some appropriate φ? Moreover\, does the algorithm converge to a minimizer of this objective function? \n3. Exact and robust recovery: Under what conditions can we recover the ground truth exactly via PnP? And is the reconstruction robust to noise in the measurements? \nWhile early work on PnP has attempted to answer some of these questions\, many of the underlying assumptions are either strong or unverifiable. This is essentially because denoisers such as BM3D and DnCNN are mathematically complex\, nonlinear and difficult to characterize. A first step in understanding complex nonlinear phenomena is often to develop an understanding of some linear approximation. In this spirit\, we focus our attention on denoisers that are linear. In fact\, there exists a broad class of real-world denoisers that are linear and whose performance is quite decent; examples include kernel filters (e.g. NLM\, bilateral filter) and their symmetrized counterparts. This class has a simple characterization that helps to keep the analysis tractable and the assumptions verifiable. Our main contributions lie in resolving the aforementioned questions for PnP algorithms where the plugged denoiser belongs to this class. We summarize them below. \n• We prove fixed-point convergence of the PnP version of ISTA under mild assumptions on the measurement model. \n• Based on the theory of proximal maps\, we prove that a PnP algorithm in fact minimizes a convex objective function f + φ\, subject to some algorithmic modifications that arise from the algebraic properties of the denoiser. Notably\, unlike previous results\, our analysis applies to non-symmetric linear filters. \n• Under certain verifiable assumptions\, we prove that a signal can be recovered exactly (resp. robustly) from clean (resp. noisy) measurements using PnP regularization. As a more profound application\, in the spirit of classical compressed sensing\, we are able to derive probabilistic guarantees on exact and robust recovery for the compressed sensing problem where the sensing matrix is random. An implication of our analysis is that the range of the linear denoiser plays the role of a signal prior and its dimension essentially controls the size of the set of recoverable signals. In particular\, we are able to derive the sample complexity of compressed sensing as a function of distortion error and success rate. \nWe validate our theoretical findings numerically\, discuss their implications and mention possible future research directions.
URL:https://ee.iisc.ac.in/event/thesis-defence-of-mr-ruturaj-gavaskar/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230102T133000
DTEND;TZID=Asia/Kolkata:20230104T223000
DTSTAMP:20260404T012224
CREATED:20221128T001914Z
LAST-MODIFIED:20221128T003251Z
UID:240127-1672666200-1672871400@ee.iisc.ac.in
SUMMARY:Workshop on Protection and Stability of Renewable Dominated Power Grids
DESCRIPTION:Click here for the poster.\nTopics that will be covered in the workshop:\n\nOverview of Photovoltaic and Wind Generations\nConverter Controls for Renewables\nGrid Connection Requirements\nImpact of Renewables on Fault Analysis and Protection\nImpact of Renewables on System Stability\nTraining on Renewable Modelling in PSCAD\nAC Microgrids\nDC Microgrids\nCase Studies\n\nThe list of speakers: (Click here for the schedule.)\n\nProf Sukumar Brahma\, Clemson University\, USA\nProf Prasad Enjeti\, Texas A&M University\, USA\nDr Ritwik Majumder\, Mathworks\nProf Vinod John\, IISc\nProf Kaushik Basu\, IISc\nProf Gurunath Gurrala\, IISc\nDr. Vishnu Mahadeva Iyer\nProf Sarasij Das\, IISc\n\n 
URL:https://ee.iisc.ac.in/event/workshop-on-protection-and-stability-of-renewable-dominated-power-grids/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221230T163000
DTEND;TZID=Asia/Kolkata:20221230T173000
DTSTAMP:20260404T012224
CREATED:20221205T053506Z
LAST-MODIFIED:20221205T053816Z
UID:240135-1672417800-1672421400@ee.iisc.ac.in
SUMMARY:Invited Talk by Prof Anjan Bose
DESCRIPTION:Title: Maintaining Reliability and Resiliency while Decarbonizing the Power Grid \nAbstract: The world has focused strongly\, through the Paris Accords\, on ridding the electricity generation mix of fossil fuels and replacing that with sustainable non-carbon resources. The emerging new generation mix\, however\, is changing the characteristics of the grid thus requiring the modification of the ways we plan\, design\, operate and control the grid. The new engineering tools and procedures must be ready as the penetration of renewable energy resources keeps increasing. These methods to provide highly reliable electricity to society were developed over decades but now must be updated more urgently. In this address we outline where these threats are coming from and how we maintain the highly reliable systems despite the changes. In addition\, the increase in extreme weather events is necessitating more efficient ways to recover from grid damage thus increasing the resiliency of the system in addition to maintaining reliability. \nAuthor’s Bio: Prof Anjan Bose (Life Fellow\, IEEE) received the B.Tech. degree from IIT Kharagpur\, Kharagpur\, India\, the M.S. degree from the University of California\, Berkeley\, CA\, USA\, and the Ph.D. degree from Iowa State University\, Ames\, IA\, USA. He has worked for industry\, academe\, and government for 40 years in electric power engineering. He is currently a Regents Professor and holds an Endowed Distinguished Professor in power engineering at Washington State University\, Pullman\, WA\, USA\, where he also served as the Dean for the College of Engineering and Architecture\, from 1998 to 2005. He is a member of the U.S. National Academy of Engineering and a Foreign Fellow of the Indian National Academy of Engineering. He received the Herman Halperin Award and the Millennium Medal from the IEEE and was recognized as a Distinguished Alumnus by IIT Kharagpur and Iowa State University
URL:https://ee.iisc.ac.in/event/invited-talk-by-prof-anjan-bose/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221220T163000
DTEND;TZID=Asia/Kolkata:20221220T173000
DTSTAMP:20260404T012224
CREATED:20221215T225256Z
LAST-MODIFIED:20221215T225552Z
UID:240183-1671553800-1671557400@ee.iisc.ac.in
SUMMARY:Thesis Colloquium of Mr. Debarpan Bhattacharya
DESCRIPTION:Degree Registered: MTech Resesarch\nTitle: A Learnable Distillation Approach For Model-agnostic Explainability With Multimodal Applications\nAdvisor: Prof. Sriram Ganapathy\nDate and Time: Tuesday\, Dec 20th \, 11am\nVenue:  MMCR\, Electrical Engineering\, IISc.\n\nAbstract: Deep neural networks are the most widely used examples of sophisticated mapping functions from feature space to class labels. In the recent years\, several high impact decisions in domains such as finance\, healthcare\, law and autonomous driving\, are made with deep models. In these tasks\, the model decisions lack interpretability\, and pose difficulties in making the models accountable. Hence\, there is a strong demand for developing explainable approaches which can elicit how the deep neural architecture\, despite the astounding performance improvements observed in all fields\, including computer vision\, natural language processing\, generates the output decisions.\n\nThe current frameworks for explainability of model learning are based on gradients (eg. GradCAM\, guided-gradCAM\, Integrated gradients etc) or based on locally linear assumptions (eg. LIME). Some of these approaches require the knowledge of the deep model architecture\, which may be restrictive in many applications. Further\, most of the prior works in the literature highlight the results on a set of small number of examples to illustrate the performance of these XAI methods\, often lacking statistical evaluation.\n\nThis talk proposes a new approach for explainability based on mask estimation approaches\, called the Distillation Approach for Model-agnostic Explainability (DAME). The DAME is a saliency-based explainability model that is post-hoc\, model-agnostic\, and applicable to any architecture/domain. The DAME is a student-teacher modeling approach\, where the teacher model is the original model for which the explainability is sought\, while the student model is the mask estimation model. The input sample is augmented with various data augmentation techniques to produce numerous samples in the immediate vicinity of the input. Using these samples\, the mask estimation model is learned to learn the saliency map of the input sample for predicting the labels. A distillation loss is used to train the DAME model\, and the student model tries to locally approximate the original model. Once the DAME model is trained\, the DAME generates a region of the input (either in space or in time-domain for images and audio samples\, respectively) that best explains the model predictions. \n\nWe also propose an evaluation framework\, for both image and audio tasks\, where the XAI models are evaluated in a statistical framework on a set of held-out of examples with the Intersection-over-Union (IoU) metric. We have validated the DAME model for vision\, audio and biomedical tasks. Firstly\, we deploy the DAME for explaining a ResNet-50 classifier pre-trained on ImageNet dataset for the object recognition task. Secondly\, we explain the predictions made by ResNet-50 classifier fine-tuned on Environmental Sound Classification (ESC-10) dataset for the audio event classification task. Finally\, we validate the DAME model on the COVID-19 classification task using cough audio recordings. In these tasks\, the DAME model is shown to outperform existing benchmarks for explainable modeling. \n\nThe talk will also illustrate results on various multimodal datasets and conclude with a discussion on the limitations of the DAME approach along with the potential future directions.\n\n######################################################################\n\nAll are welcome\,\n\n\n\n 
URL:https://ee.iisc.ac.in/event/thesis-colloquium-of-mr-debarpan-bhattacharya/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221213T203000
DTEND;TZID=Asia/Kolkata:20221213T213000
DTSTAMP:20260404T012224
CREATED:20221212T221650Z
LAST-MODIFIED:20221212T221650Z
UID:240170-1670963400-1670967000@ee.iisc.ac.in
SUMMARY:Lecture by Dr. Raveesh Magod
DESCRIPTION:Title: Powering the Future – Research and Current Trends Shaping the Next Generations of Power Management ICs \nDate and Time: 13th December 2022 at 3pm \nVenue: MMCR EE \nAbstract: Power management has been a key enabler for a variety of ever increasing modern day electronic applications like smartphones\, data center servers\, electric vehicles and smart grids to name a few. High-efficiency\, small form-factor\, reliability and lower cost will continue to be critical requirements of power regulation for such applications. In this talk\, details about what constitutes this broad area of power management along with research vectors and market trends defining the next-generation ICs in power conversion is presented. Specifically i) ultra-low power consumption converters ii) Gallium Nitride (GaN) and Silicon Carbide (SiC) based power converters and iii) low noise and low EMI power conversion\, are identified and described as three major focus areas. Personal research contributions\, insights into latest research and industry products\, and future performance trendlines are presented in detail. \nSpeaker Bio: Raveesh Magod received the M.S. and Ph.D. degree in Electrical engineering from Arizona State University\, Tempe\, AZ\, USA\, in 2014 and 2018 respectively. In 2017\, he joined Jack Kilby Labs\, Texas Instruments\, Dallas\, TX\, USA\, where he is Member of Technical Staff and has been involved in R&D of wide range of power converter products ranging from nanopower voltage regulators to high power-density DC-DC converters and recently has been focusing on GaN based power converters. From 2015 to 2016\, he was an analog design intern at Texas Instruments\, Tucson\, AZ\, USA\, where he designed low-power voltage supervisors and low quiescent current LDOs. From 2010 to 2012\, he was a Design Engineer at Sankalp Semiconductor (A HCL technologies company)\, Hubli\, India\, developing low-power CMOS interface solutions. He was the co-recipient of A.K. Chowdhary Best Paper award at the International conference on VLSI Design\, 2021 and has five granted/pending U.S. patents to his name. He also serves as a technical program committee member for the CICC and a reviewer for multiple reputed IEEE journals.
URL:https://ee.iisc.ac.in/event/lecture-by-dr-raveesh-magod/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221209T213000
DTEND;TZID=Asia/Kolkata:20221209T223000
DTSTAMP:20260404T012224
CREATED:20221207T000049Z
LAST-MODIFIED:20221207T000049Z
UID:240140-1670621400-1670625000@ee.iisc.ac.in
SUMMARY:Seminar by Dr. Subhash Lakshminarayana
DESCRIPTION:Title: IoT-Based Load-Altering Attacks Against Power Grids\nDate: 09-12-2022\, Friday\nTime: 4:00 PM – 5:00 PM\nVenue: MMCR of EE Department\, Room No: C-241 (First floor) \nAbstract: Large-scale Internet of Things (IoT)-based load-altering attacks can have a major impact on power grid operations such as causing unsafe frequency excursions and destabilizing the grid’s control loops. In this talk\, I will present my recent research on enhancing the resilience of power grids to IoT-based load-altering attacks. First\, I will present a novel analytical framework to investigate the impact of IoT-based static/dynamic load-altering attacks (S/DLAAs) on the power grid’s dynamic response using the theory of second-order dynamical systems. The results help identify the victim nodes from which that attacker can launch the most impactful attacks and offer insights into how the temporal fluctuations of load and renewable energy sources impact the grid’s vulnerabilities to LAAs. Finally\, I will present results on the detection and mitigation of such attacks. \nBiography: Dr. Subhash Lakshminarayana is an associate professor at the University of Warwick. His research interests include cyber-physical system security and wireless communications. He serves as an associate editor in the IET Smart Grid journal. His research is funded by Innovate UK\, EPSRC-PETRAS National Centre of Excellence for Cybersecurity of IoT Systems UK\, and the EUTOPIA European Alliance.
URL:https://ee.iisc.ac.in/event/seminar-by-dr-subhash-lakshminarayana/
LOCATION:EE\, MMCR
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221123T153000
DTEND;TZID=Asia/Kolkata:20221123T163000
DTSTAMP:20260404T012224
CREATED:20221115T032528Z
LAST-MODIFIED:20221115T032641Z
UID:240120-1669217400-1669221000@ee.iisc.ac.in
SUMMARY:Thesis Colloquium of Mr  Bidhan Biswas
DESCRIPTION:Degree  Registered:   Ph.DThesis Title:                Short Circuit and Open Circuit Natural Frequencies of 3-Φ Transformers: Derived Analytical Expressions and its ApplicationsGuide:                          Prof. L. Satish\nDate & Time:               Wednesday\, 23 November 2022\, at 10:00 AM\nVenue:                         Hybrid Mode\, on MS TEAMS and held in HV Seminar Hall\n\n\nAbstract: Frequency Response Analysis (FRA) method is perhaps the most sensitive tool that can detect even the slightest of winding/core movements. High sensitivity\, non-invasiveness\, non-destructiveness\, and on-site capability are some of its salient features – making it an ideal monitoring and detection tool. The existence of Standards (IEEE\, IEC\, and CIGRE) is ample testimony of its global acceptance and superior detection capabilities. The principle of detection is based on observance of a deviation between two measured FRAs which implies a possible fault. Naturally\, the next logical step is to analyse these deviations to determine the type of fault\, estimate the extent of damage and its severity\, and as a bonus\, predict its location\, if possible. However\, even after three decades of existence\, arriving at these inferences  is still at the research level. Even though there is a consensus among all the standards on FRA test/measurement procedures\, best-suited terminal connections\, cable layout\, grounding practices\, etc.\, they remain largely silent regarding interpretation and diagnostics.\n\n\n\nA detailed analysis of literature compiled in Chapter 1 reveals that perhaps lack of a mathematical foundation might be one reason for the present plight of FRA. So\, developing a generic mathematical-based approach for interpretation and location of  incipient mechanical winding damages in actual 3-Φ transformer windings\, using measured FRA\, is imperative. Development of a such generic method necessitates derivation of closed-form expressions which can provide a direct link between measured FRA quantities to the electrical parameters of the winding. For assessing damage severity\, the challenge is to identify a quantity which is not only extractable from measured FRA\, but also be sensitive\, monotonic\, and traceable to the fault. Driven by this philosophy this thesis aims to address the following –\n\n\n\n•   Propose a unified and general approach to derive closed-form analytical expressions (for each multiphase winding) to link the measured open and short circuit natural frequencies to electrical parameters of the winding\, and valid for any condition of the neutral•   Define a quantity calculable from the measured FRA’s peak/trough frequencies which is physically related to mechanical damage in the winding\, and perhaps yield some physical insight about damage•   Develop novel methods using the derived analytical expressions to identify an incipient\, discrete\, and localized axial and/or radial displacement in any multiphase winding\, and applicable for any condition of the neutral\n\n\n\nIn the second chapter\, a generic and unified analytical method is developed (applicable to any 1-Φ or 3-Φ winding) starting from the basic mutually coupled lossless ladder network model to derive equations which relate the harmonic sum of squares of short circuit natural frequencies (SCNF) and open circuit natural frequencies (OCNF) to the elemental winding inductances and capacitances. Complete details of the derivation are discussed\, and all the derived formulae were cross verified by extensive numerical circuit simulations.\n\n\n\nEach one of these derived expressions has a strikingly similar structure and possesses a unique property viz.\, the contribution of series capacitances and ground capacitances are decoupled. This important property paves way for estimating a physical quantity that is directly responsible for the winding resonances\, viz.\, the effective air-core inductance (Leff). This estimation requires multiple FRA measurements. Chapter 3 presents complete details of the concept\, its derivation\, measurements\, and experimental results are for all 1-Φ and 3-Φ windings.\n\n\n\nLoss of clamping pressure in a winding is not directly identifiable by any means\, other than an FRA measurement. But\, this damage cannot be judged by merely comparing two FRAs. So\, a clamping pressure measurement experiment was carried out on a single isolated winding to ascertain the sensitivity and monotonicity afforded by the quantity\, Leff\, to a change in clamping pressure. Driven by the promising results\, author proceeds to build a method based on Leff to find the location of a discrete and localized axial displacement (AD) in any 3-Φ winding configuration. Details of this method\, experimental results\, and measurement steps are presented in Chapter 4.\n\n\n\nProceeding further\, Chapter 5 discusses concept of a new method\,  measurement steps and experimental results to identify presence of a Radial Displacement (RD) in a 3-Φ star winding with neutral-open\, as well as\, in a delta connected winding. Driven by success\, the concept was extended to identify the simultaneous occurrence of a discrete and localized AD and RD in one phase of a 3-Φ star winding\, with neutral-open. Preliminary experimental results proved the method can successfully identify faulted phases that contained AD and RD.\n\n\n\nAll experiments reported in the thesis were carried out on transformer windings rated at 33 kV\, 3.5 MVA. The results are encouraging and the author believes that true potential of the proposed methods can be judged when implemented on actual transformers.\n\n\n\nIn summary\, this thesis presents\, perhaps for the first time\, a mathematical basis for identifying and diagnosing axial and radial displacements in 1-Φ and 3-Φ windings using the peak/trough frequency data from the measured FRA. The author believes that this is a small step forward in advancing FRA as a diagnostic tool.\n\n* * * * * * * * * * ALL ARE CORDIALLY INVITED * * * * * * * * *
URL:https://ee.iisc.ac.in/event/thesis-colloquium-of-mr-bidhan-biswas/
LOCATION:HV seminar Hall
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221118T200000
DTEND;TZID=Asia/Kolkata:20221118T210000
DTSTAMP:20260404T012224
CREATED:20221109T234238Z
LAST-MODIFIED:20221109T234314Z
UID:240117-1668801600-1668805200@ee.iisc.ac.in
SUMMARY:Thesis Defence of Mr. Unni V S
DESCRIPTION:Degree Registered: PhD (Engg). \nGuide: Prof. Kunal Narayan ChaudhuryDate: November 18\, 2022.Time: 2:30 pm.Venue: Online.Link: MS Teams link: https://tinyurl.com/yr96memmTitle: Efficient and Convergent Algorithms for High-Fidelity Hyperspectral Image Fusion.Abstract: Hyperspectral (HS) imaging refers to acquiring images with hundreds of bands corresponding to different wavelengths of light. HS imaging has a wide range of applications such as remote sensing\, industrial inspection\, environmental monitoring\, etc. A fundamental consideration with multiband sensors is that the amount of incident energy is limited and this creates an intrinsic tradeoff between spatial resolution and the number of bands—current optical sensors can either generate images with high resolution but a small number of bands or images with a large number of bands but reduced resolution. For example\, HS images have hundreds of bands but low spatial resolution\, whereas the opposite is true for multispectral (MS) images. An extreme case is a panchromatic (PAN) image with very high spatial resolution but just a single band. Image fusion refers to techniques where multiband images with high spatial resolution are synthetically generated using image processing algorithms. It includes pansharpening (MS+PAN)\, hyperspectral sharpening (HS+PAN)\, and HS-MS fusion (HS+MS). Reconstructing a fused image from the observed images is ill-posed and needs regularization. Diverse regularization methods have been proposed over the years for general imaging problems\, many of which perform very well for fusion. This includes vector total variation\, sparsity and dictionary-based penalties\, generalized Gaussian- and GMM-based priors\, etc. This thesis proposes novel regularization models and algorithms that can outperform state-of-the-art image fusion techniques. We can broadly group these into two classes—explicit and implicit regularization.Explicit regularization refers to the design of hand-crafted penalty functions that impose desirable properties (e.g.\, smoothness) on the reconstruction; this is used along with the observed data for fusion. We propose a convex regularizer that is motivated by nonlocal patch-based methods for image restoration. Our regularizer accounts for long-distance correlations in hyperspectral images\, considers patch variation for capturing texture information\, and uses the higher resolution image for guiding the fusion process. Unlike local pixel-based methods\, where variations along just horizontal and vertical directions are penalized\, we use a wider search window in terms of nonlocality and directionality. This is shown to yield state-of-the-art results. The catch is that the resulting optimization problem is non-differentiable and we cannot use simple gradient-based algorithms. However\, we show that by expressing patch variation as filtering operations and judiciously splitting the original variables and introducing latent variables\, we develop a provably convergent iterative algorithm\, where the subproblems can be solved efficiently using FFT-based convolution and soft-thresholding.In the implicit approach\, we rely on a recent paradigm known as plug-and-play (PnP) regularization\, where powerful off-the-shelf denoisers are used for regularization purposes. While this has been shown to give state-of-the-art results for general restoration tasks\, it has not so much been explored for fusion. In fact\, we faced few technical challenges in applying PnP for hyperspectral fusion. Firstly\, existing denoisers are slow when applied to multiband images and we need to apply such denoisers several times with the PnP framework. Secondly\, convergence is generally not guaranteed for PnP regularization since the mechanism is ad-hoc. Along with efficiency and good denoising performance\, we need to come up with a denoiser with specific properties that can guarantee convergence. We proposed a couple of approaches to solve this problem. In the first approach\, we have developed a high-dimensional kernel denoiser with low cost yet good denoising performance\, which can guarantee PnP convergence. The overall algorithm is fast and competitive with state-of-the-art methods. In the second approach\, we leverage the power of deep learning to develop a trained patch denoiser which has a couple of advantages over conventional end-to-end learning: (1) Unlike end-to-end networks which require excessive ground-truth data for training\, we can be trained the denoiser from patches extracted from the observed images. For example\, in HS+MS fusion\, the MS image captures the same scene and has the same spatial resolution as the target image. We train the denoiser by sampling clean patches from the MS image and corrupting them with noise.(2) Compared to end-to-end learning\, where the training is done with a fixed forward model\, our method can be deployed for different forward models. This is possible thanks to the decoupling of the inversion (of the forward model) and denoising steps in PnP.We use the trained denoiser for PnP regularization and establish convergence of the PnP iterations under a technical assumption that we verify numerically. As far as the reconstruction quality is concerned\, our method outperforms state-of-the-art variational and deep-learning fusion techniques.
URL:https://ee.iisc.ac.in/event/thesis-defence-of-mr-unni-v-s/
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221114T160000
DTEND;TZID=Asia/Kolkata:20221114T170000
DTSTAMP:20260404T012224
CREATED:20221102T044553Z
LAST-MODIFIED:20221102T045520Z
UID:240090-1668441600-1668445200@ee.iisc.ac.in
SUMMARY:Thesis Defence of Meshineni Deepchand
DESCRIPTION:Degree Registered:              M.Tech(Res).\nGuide:                                    Dr. Rathna G N\nVenue:                                    MMCR EE\, C 241\nDate & Time:                         14th November 10:30am \nTeams meeting link: Click here to join the meeting \nTitle:    Non contact Breathing and Heartbeat signals monitoring using FMCW radar \nAbstract: Non-contact breathing and heartbeat signals monitoring are the tasks of extracting them without contact sensors. It became even more critical in COVID 19\, and hence it is crucial to estimate them correctly. FMCW (Frequency Modulated Continuous Wave) radar is employed to estimate these two signals without contact. Radar captures chest displacement and body movement. Because of this\, breathing and heartbeat signals are distorted. The reduction of false peaks and peak estimation is crucial for breathing rate calculation. So in this thesis\, firstly\, we propose a novel way for tracing body movement and eliminating the traced segment for breathing and heart rate calculation. In the second part\, we efficiently reduced false peaks using maximal overlap discrete wavelet transform (MODWT) to decompose and reconstruct the filtered breathing signal for estimating breathing rate. The heartbeat signal is estimated using bandpass filtering of unwrapped phase. We also compared our algorithm with the task force monitoring (TFM) device as a reference and discussed its performance. Also\, our proposed method for breathing rate estimation has an accuracy of 92.43% and heartrate estimation it is 85.16%. \n* * * * * * * * ALL ARE CORDIALLY INVITED * * * * * * * *
URL:https://ee.iisc.ac.in/event/thesis-defence-of-meshineni-deepchand/
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221111T170000
DTEND;TZID=Asia/Kolkata:20221111T170000
DTSTAMP:20260404T012224
CREATED:20221107T014902Z
LAST-MODIFIED:20221107T025832Z
UID:240109-1668186000-1668186000@ee.iisc.ac.in
SUMMARY:Lecture by Dr. Ganesh Sivararaman
DESCRIPTION:Indian Institute of Science and\nThe IEEE Signal Processing Society\, Bangalore Chapter\nCordially invites you to the following talk on\n“Unsupervised adaptation in speech technologies”\n(Click here for the poster.) \nSpeaker: Dr. Ganesh Sivaraman\, Pindrop\, Atlanta\, USA\nDate and Time: 11th November 2022 at 11:30am to 12:30pm\nVenue: MMCR (Room No. C241)\, 1st Floor\, Dept. of Electrical Engineering \nAbstract: Unsupervised learning and adaptation techniques have taken center stage due to the exponential growth of unlabeled data. For many practical applications unsupervised learning helps in the adaptation of machine learning systems to mismatched train and test domains. Unsupervised adaptation can be performed by three broad approaches – 1) feature transformations in the test domain\, 2) model adaptation to test domain\, and 3) generation of synthetic test domain samples. This talk will outline these methods by showing three specific examples from speech processing. Unsupervised speaker adaptation for acoustic-to-articulatory speech inversion serves as an example of feature transformation-based adaptation. Adaptation of end-to-end ASR systems without manual transcriptions will be presented as an example of model adaptation. Finally\, children’s speech simulation for zero-shot child speech classification using X-vectors will be presented as an example of synthetic data generation for the test domain. \nBiography:  Ganesh Sivaraman is a Senior Research Scientist at Pindrop\, in Atlanta\, USA. He received his M.S. (2013) and Ph.D. (2017) in Electrical Engineering from the University of Maryland College Park. His research experience and publications span several speech technologies like acoustic-to-articulatory inversion\, ASR\, speaker recognition\, deepfake detection\, and speech enhancement. During his PhD at Maryland\, he was awarded the Future Faculty Fellowship\, and the International Graduate Research Fellowship by the A. James Clark School of Engineering. Along with his official work\, he is actively involved in teaching\, mentoring\, and collaborating with doctoral students at Maryland. Apart from research work\, Ganesh is a fluent speaker of Sanskrit actively learning and teaching the language as a volunteer of Samskrita Bharati USA. He is passionate about creating computational tools for learning Sanskrit pronunciation.
URL:https://ee.iisc.ac.in/event/lecture-by-dr-ganesh-sivararaman/
LOCATION:EE\, MMCR
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221111T150000
DTEND;TZID=Asia/Kolkata:20221111T160000
DTSTAMP:20260404T012224
CREATED:20221106T232123Z
LAST-MODIFIED:20221106T233337Z
UID:240104-1668178800-1668182400@ee.iisc.ac.in
SUMMARY:Thesis Colloquium of Sayantan Das
DESCRIPTION:Thesis Title:  Modeling of lightning attachment to aircraft and  quantification of the influencing parameters \nGuide: Prof. Udaya Kumar \nDegree registered:          Ph.D. \nDate and Time:              11th November 2022\, 9:30 AM\nMeeting link:                  https://teams.microsoft.com/l/meetup-join/19%3ameeting_MDg5YzdhYWUtMTc3Zi00Yjg0LWE1ZTktYjgyY2I5Y2MyNDI4%40thread.v2/0?context=%7b%22Tid%22%3a%226f15cd97-f6a7-41e3-b2c5-ad4193976476%22%2c%22Oid%22%3a%227ef4df52-6005-46aa-bff3-d96db1a85b71%22%7d \nAbstract: According to Air Transport Action Group (ATAG)\, 45 million aircraft took off worldwide in 2020\, which translates to 1.5 lakh per day. Statistically\, the aviation industry is found to double its fleet size every fifteen years. Lightning is considered one of the dreadful environmental threats to aircraft. Past incidents show that lightning strikes can lead to structural damage\, operational interruption\, and loss of lives. Field data suggest that\, on average\, an aircraft gets struck by lightning once or twice a year. Therefore\, the threat due to lightning is considered a crucial safety aspect of an aircraft. \nDesign of suitable lightning protection for aircraft involves Zoning of its skin. It is intended to differentiate lightning attachment points\, channel slipping regions\, and regions that carry just the stroke current. The first step of Aircraft Zoning is to identify the initial attachment points. For the same\, different methods like Laboratory experiments\, similarity principle\, Rolling Sphere Method (RSM)\, and Field-based approach are suggested in the standard ARP5414. In reality\, the lightning strikes to aircraft can be of two modes\, Aircraft-initiated and Aircraft-intercepted. In the former one\, under the influence of a thundercloud or descending lightning leader\, the aircraft initiates stable bipolar connecting leaders\, upward and downward leader toward the ground. These leaders are deemed to propagate hundreds of meters to complete the lightning strike. In Aircraft-intercepted strikes\, the aircraft intercepts a descending lightning leader and hence gets struck. The laboratory experiments on scaled aircraft models or isolated aircraft parts are inadequate to assess the initial attachment points. The similarity principle suggested in the standard is qualitative and can’t be extended to aircraft of any size and shape. The 25m Rolling Sphere Method (RSM) is routinely employed to determine the attachment points. This method doesn’t consider the connecting leader discharges from aircraft and therefore overestimates the possible attachment points. Most (90%) of the lightning strikes to aircraft are attributed to aircraft-initiated mode\, which involves significant connecting leader activities. Therefore\, it has to be traced accurately to assess attachment points. \nIn literature\, it is difficult to find a model for bipolar leader discharges from aircraft. However\, work on either negative or positive leader inception and propagation from laboratory gaps and their extension can be relatively found. Based on them\, the present work aims to develop a suitable model for simulating bipolar leader discharges from aircraft. Additionally\, the aircraft-intercepted mode of lightning strikes is also included. In summary\, a novel model adapting the pertinent physical aspects of the leader discharges has been developed to accurately assess initial lightning attachment points to aircraft.  \nUsing the model developed\, the following practically important questions are addressed:  \n\nDependency of the frequency of lightning strikes to aircraft on its shape and size.\nRate of lightning strikes to aircraft at different altitudes\nFor a given aircraft and its route\, the number of times it gets struck by lightning\nThe average number of strikes to an aircraft per year\n\nTo present a quantitative assessment\, two different aircraft models\, McDonnell Douglas DC-10 and Standard Dynamic Model are considered. \nIn summary\, a novel model based on physical grounds has been developed to assess the initial lightning attachment points on aircraft. Using the same\, further methodologies are constructed to quantify the dependency of the strike rate on aircraft size\, altitude\, and possible average strike rate. \nALL ARE WELCOME
URL:https://ee.iisc.ac.in/event/thesis-colloquium-of-sayantan-das/
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221109T193000
DTEND;TZID=Asia/Kolkata:20221109T203000
DTSTAMP:20260404T012224
CREATED:20221103T232724Z
LAST-MODIFIED:20221103T233801Z
UID:240097-1668022200-1668025800@ee.iisc.ac.in
SUMMARY:Lecture by Prof. Carlos Busso
DESCRIPTION:Organised by\nIndian Institute of Science and\nThe IEEE Signal Processing Society\, Bangalore Chapter\nTitle: Robust Emotion Recognition (Click here for the poster)\nDate and Time: 9th November 2022 at 2:00pm\, Refreshments: 3:00pm\nVenue: MMCR (Room No. C241\, 1st Floor\, Dept. of Electrical Engineering \nAbstract of the talk: It is challenging to achieve robust and well-generalized models for tasks involving subjective concepts such as emotion. This tech talk will describe novel approaches to effectively develop robust speech emotion recognition (SER) systems. At the resource level\, we will describe our effort to collect the MSP-Podcast corpus\, which is a large\, naturalistic emotional database. The data collection protocol combines machine-learning algorithms to retrieve recordings conveying balanced emotional content annotated with a cost-effective crowdsourcing protocol. To improve the temporal modeling of SER systems\, this seminar will also discuss a novel dynamic chunking approach that maps the sequences of different lengths into a fixed number of chunks that have the same duration by adjusting their overlap. This simple chunking procedure creates a flexible framework\, facilitating parallel computing. The approach can incorporate different feature extractions and sentence-level temporal aggregation approaches to cope\, in a principled way\, with a sequence-to-one SER task. Likewise\, the seminar will discuss multimodal pre-text tasks that are carefully designed to learn better representations for predicting emotional cues from speech\, leveraging the relationship between acoustic and facial features. Finally\, the seminar will discuss our current effort to design multimodal emotion recognition strategies that effectively combine auxiliary networks\, a transformer architecture\, and an optimized training mechanism for aligning modalities\, capturing temporal information\, and handling missing features. These models offer principled solutions to increase the generalization and robustness of emotion recognitions  systems. \nSpeaker Biography: Carlos Busso received his PhD degree (2008) in electrical engineering from the University of Southern California (USC)\, Los Angeles\, in 2008. He is a professor at the Electrical Engineering Department of The University of Texas at Dallas (UTD). At UTD\, he leads the Multimodal Signal Processing (MSP) laboratory [http://msp.utdallas.edu]. He is a recipient of an NSF CAREER Award. In 2014\, he received the ICMI Ten-Year Technical Impact Award. In 2015\, his student received the third prize IEEE ITSS Best Dissertation Award (N. Li). He also received the Hewlett Packard Best Paper Award at the IEEE ICME 2011 (with J. Jain)\, and the Best Paper Award at the AAAC ACII 2017 (with Yannakakis and Cowie). He received the Best of IEEE Transactions on Affective Computing Paper Collection in 2021 (with R. Lotfian) and in 2022 (with Yannakakis and Cowie). He is the co-author of the winner paper of the Classifier Sub-Challenge event at the Interspeech 2009 emotion challenge. His research interest is in human-centered multimodal machine intelligence and applications. His current research includes the broad areas of affective computing\, multimodal human-machine interfaces\, nonverbal behaviors for conversational agents\, in-vehicle active safety system\, and machine learning methods for multimodal processing. His work has direct implication in many practical domains\, including national security\, health care\, entertainment\, transportation systems\, and education. He was the general chair of ACII 2017 and ICMI 2021. He is a member of ISCA\, AAAC\, and a senior member of ACM and IEEE.
URL:https://ee.iisc.ac.in/event/lecture-by-prof-carlos-busso/
LOCATION:EE\, MMCR
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20221107T200000
DTEND;TZID=Asia/Kolkata:20221107T220000
DTSTAMP:20260404T012224
CREATED:20221102T034842Z
LAST-MODIFIED:20221102T042355Z
UID:240082-1667851200-1667858400@ee.iisc.ac.in
SUMMARY:Online Thesis Defence of Ashiq Muhammed P E
DESCRIPTION:Degree Registered:              Ph.D.\nGuide:               Prof. Satish L and Prof. Udaya Kumar\nThesis Title:     Improved Understanding of Standing Waves in Single Layer Coil and Elegant Methods to Estimate Transformer Winding Parameters \nClick here to join the Meeting \nAbstract: Analyzing the effect of impulse voltages (like lightning\, switching) on transformer winding has occupied centerstage in core electrical engineering research for over a century. These investigations gather great significance and relevance as it eventually governs the design of insulation in the winding. Notwithstanding the colossal contribution this domain has witnessed from stalwarts in the past century\, a closer scrutiny surprisingly reveals that there still exists tiny grey areas that demands attention. Pursuing this line of thought\, the first part of this thesis aims to clearly describe what this grey area is and resolving it would provide a deeper insight about fundamental understanding of surge response in transformer windings – with special emphasis on its standing wave phenomenon. Following this\, in the latter part\, elegant procedures are stitched together to determine a few electrical parameters of the transformer winding equivalent circuit that have the potential to help in assessing mechanical status of windings. Objectives of the thesis are – \n1.    Formulate an analytical method to determine the exact shape of standing waves for all modes in a uniform single layer coil as a solution of its governing partial differential equation2.    Estimate series capacitance of a uniform transformer winding from its measured driving point impedance3.    Determine effective air-core inductance of an iron-core uniform winding as a function of its axial length from measured driving point impedance \nFirst part of the thesis revisits a century-old classical theory of standing waves on uniform single layer coils. Accurate information about natural frequencies and shapes of the corresponding standing waves are essential for gaining a deeper understanding of the response of coils to impulse excitations. Analytical studies on coils have largely been based on the assumption that standing waves are sinusoids in both space and time. However\, this contradicts the results from numerical circuit analysis and practical measurements. So\, this thesis attempts to bridge this discrepancy by revisiting the classical standing wave phenomena in coils. It not only assesses the reason for the aforementioned inconsistency\, but also makes a contribution by analytically deriving the exact mode shape of standing waves for both neutral open/short conditions. For this\, the coil is modelled as a distributed network of elemental inductances and capacitances\, while an exponential function describes the spatial variation of mutual inductance between turns. Initially\, an elegant derivation of the governing partial differential equation (in terms of voltage as the variable instead of flux) for surge distribution is presented and to the best of our knowledge\, for the first time\, an analytical solution for the same has been found by the variable-separable method to find the complete solution (sum of time and spatial terms). Hyperbolic terms in the spatial part of the solution have always been neglected but are included here\, thus\, yielding the exact mode shapes. For verification\, both voltage and current standing waves computed from the analytical solution were plotted and compared with PSPICE simulation results on a 100-section ladder network representing a uniform single-layer coil. Then\, practical measurements were made on a tailor-made large-sized single layer coil with a length of 2.02 m\, diameter of ~1 m and having 640 turns. It turns out that even in such simple single layer coils\, the shape of standing waves of all modes deviates considerably from being sinusoidal. It was further observed that this deviation depends on spatial variation of mutual inductance\, capacitive coupling\, and order of the standing waves. \nIn the second part\, an elegant method for determining the series capacitance (Cs) and air-core equivalent inductance of a uniform winding as a function of its axial length (termed as M0x in this thesis) of a uniform transformer winding\, from its measured DPI magnitude\, is discussed. Knowledge about the series capacitance of the winding is essential\, which along with shunt capacitance\, determines the initial impulse voltage distribution when a surge impinges on the winding. Unlike previously published approaches\, the proposed method does not involve any cumbersome and time-consuming curve-fitting or running of optimization/search algorithms. Neither does it require winding geometry data. The proposed procedure for finding series capacitance relies on a property that is observable in the driving point impedance (DPI) function of a lossless winding with an open neutral condition\, viz.\, the ratio of the product of squares of open circuit natural frequencies to the product of squares of short circuit natural frequencies bears a particular relation to the coefficients of the DPI function. A simple procedure involving a deft manipulation and combination of a few well-known properties that correlate the roots of a polynomial to its coefficients are then utilized for determining series capacitance. \nKnowledge about equivalent air-core inductance distribution as a function of its axial length (i.e.\, M0x) is useful for localizing a minor/incipient mechanical fault in the winding. A physically realizable empirical relationship to estimate M0x is initially proposed. The corresponding constants of the empirical relationship are then calculated from the measured DPI. The proposed method requires three DPI measurements: one with neutral-end open and the other with neutral-end shorted. The third DPI is measured with a known external lumped capacitance connected between the neutral and ground. This method requires only the first few dominant natural frequencies observable in the first two of the DPIs. \nFeasibility of proposed methods for estimating Cs and M0x was initially verified by simulation on an N-section ladder network and then by experiments on small-sized continuous-disk and interleaved-disk windings\, and finally on a large-sized 33 kV\, 3.5 MVA continuous-disk winding. Salient features of the proposed methods are – they are simple\, elegant and involve minimum post-processing after measuring the DPI. Given its inherent simplicity and their relevance\, the author is hopeful that industry will come forward to implement these procedures on an existing FRA measuring instruments – thus opening a new dimension to FRA measurements. \n* * * * * * * * ALL ARE CORDIALLY INVITED * * * * * * * *
URL:https://ee.iisc.ac.in/event/thesis-defence-of-ashiq-muhammed-p-e/
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