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X-WR-CALDESC:Events for EE
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TZID:Asia/Kolkata
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TZOFFSETFROM:+0530
TZOFFSETTO:+0530
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DTSTART:20230101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230124T163000
DTEND;TZID=Asia/Kolkata:20230124T173000
DTSTAMP:20260404T141033
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/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230125T163000
DTEND;TZID=Asia/Kolkata:20230125T173000
DTSTAMP:20260404T141033
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:20230215T223000
DTEND;TZID=Asia/Kolkata:20230215T233000
DTSTAMP:20260404T141033
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:20230217T213000
DTEND;TZID=Asia/Kolkata:20230217T223000
DTSTAMP:20260404T141033
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:20230220T153000
DTEND;TZID=Asia/Kolkata:20230220T183000
DTSTAMP:20260404T141033
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:20230220T213000
DTEND;TZID=Asia/Kolkata:20230221T003000
DTSTAMP:20260404T141033
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:20230222T143000
DTEND;TZID=Asia/Kolkata:20230222T163000
DTSTAMP:20260404T141033
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;VALUE=DATE:20230223
DTEND;VALUE=DATE:20230226
DTSTAMP:20260404T141033
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:20230304T143000
DTEND;TZID=Asia/Kolkata:20230304T223000
DTSTAMP:20260404T141033
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;TZID=Asia/Kolkata:20230309T143000
DTEND;TZID=Asia/Kolkata:20230310T043000
DTSTAMP:20260404T141033
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:20230310T163000
DTEND;TZID=Asia/Kolkata:20230313T183000
DTSTAMP:20260404T141033
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:20230327T210000
DTEND;TZID=Asia/Kolkata:20230327T230000
DTSTAMP:20260404T141033
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:20230410T210000
DTEND;TZID=Asia/Kolkata:20230410T230000
DTSTAMP:20260404T141033
CREATED:20230410T000426Z
LAST-MODIFIED:20230410T001059Z
UID:240584-1681160400-1681167600@ee.iisc.ac.in
SUMMARY:Thesis colloquium of Mr. Anoop C. S.
DESCRIPTION:Advisor               : Prof. A. G. Ramakrishnan\n\nDate and Time: 10 April 2023 (Monday) 3:30 PM\n\n\n\nmeeting link: \n  \n\n\n\n\n\n\n\n\nJoin conversation\nteams.microsoft.com\n\n\n\n\n\n\n\nTITLE: Automatic speech recognition for low-resource Indian languages\n\nBuilding good models for automatic speech recognition (ASR) requires large amounts of annotated speech data. Most Indian languages are low-resourced and lack enough training data to build robust and efficient ASR systems. However\, many have an overlapping phoneme set and a strong correspondence between their character sets and pronunciations. In this thesis\, we exploit such similarities among the Indian languages to improve speech recognition in low-resource settings.\n\nSignificant contributions of the thesis:\n\nExploiting the pronunciation similarities across multiple Indian languages through shared label sets: \n\nWe propose the use of a common set of tokens across multiple Indian languages and analyze their performance in mono and multilingual settings.\n\n\nWe find that the Sanskrit Library Phonetic Encoding (SLP1) tokens\, which exploit the pronunciation-based structuring of character Unicodes in Indian languages\, perform better than some other grapheme-to-phoneme (G2P) based tokens in monolingual ASR settings.\nSyllable-based sub-words perform better than the character-based token units in monolingual speech recognition. However\, character-based SLP1 tokens perform better in cross-lingual transfer.\n\n\nStrategies for improving the performance of ASR systems in low-resource scenarios (target languages) exploiting the annotated data from high-resource languages (source languages):\n\nWe study three different low-resource settings:\n\nA) Labelled audio data is not available in the target language. Only a limited amount of unlabeled data is available. We adopt the unsupervised domain adaptation (UDA) schemes popular in image classification problems to tackle this case.\n\n\nThe adversarial training with gradient reversal layers (GRL) and domain separation networks (DSN) provides word error rate (WER) improvements of 6.71% and 7.32% in Sanskrit compared to a baseline hybrid DNN-HMM system trained on Hindi.\nThe UDA models outperform multi-task training with language recognition as the auxiliary task.\nSelection of the source language is critical in UDA systems.\n\n\nB) Target language has only a small amount of labeled data and has some amount of text data to build language models. We try to benefit from the available data in high-resource languages through shared label sets to build unified acoustic (AM) and language models (LM).\n\n\nUnified language-agnostic AM + LM performs better than monolingual AM + LM in cases where (a) only limited speech data is available for training the acoustic models and (b) the speech data is from domains different from that used in training.\nIn general\, multilingual AM + monolingual LM performs the best.\n\n\nC) There are N target languages with limited training data and several source languages with large training sets. Here\, we establish the usefulness of model-agnostic meta-learning (MAML) pre-training in Indian languages and propose improvements with text-similarity-based loss-weightings.\n\n\nMAML beats joint multilingual pretraining by an average of 5.4% in CER and 20.3% in WER.\nWith just 25% of the data\, MAML performance matches joint multilingual models trained on the whole target data.\nSimilarity with the source languages impacts the target language’s ASR performance.\nWe use text-similarity measured through cosine and Mahalanobis distances to weigh the losses during MAML pretraining. It yields a mean absolute improvement of 1% in WER.\n\n\n\n\n\n                                       ALL ARE WELCOME ONLINE!
URL:https://ee.iisc.ac.in/event/thesis-colloquium-of-mr-anoop-c-s/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230417T210000
DTEND;TZID=Asia/Kolkata:20230417T230000
DTSTAMP:20260404T141033
CREATED:20230409T224041Z
LAST-MODIFIED:20230412T233135Z
UID:240578-1681765200-1681772400@ee.iisc.ac.in
SUMMARY:Ph.D. Thesis colloquium of Ms. Ritika Jain
DESCRIPTION:Advisor: Prof. A. G. Ramakrishnan  \n\n\n   \n\n\nTITLE: Multimodal sleep staging and diagnosis of sleep disorders \n MS Teams link   \n\n\nSleep staging is a tedious and time-consuming process carried out manually by clinicians in which they annotate overnight polysomnograph recordings. An automated sleep scoring system can perform faster and objective sleep staging. Methods are proposed to classify the sleep EEG data into multiple stages by utilizing temporal\, spectral\, time-frequency\, non-linear\, and statistical features and random undersampling with boosting technique (RUSBoost) on a decision tree classifier. The role of data augmentation and temporal context on classifier performance is evaluated for healthy controls and clinical populations. This work also attempts to classify different sleep disorders using single-channel EEG and evaluate the role of individual sleep stages in that task.  \n\n\n  \n\n\nSignificant contributions of the thesis:         \n\n\n        \n\n\nBinary classification of sleep and wake states for healthy individuals and clinical population:   \n\n\n\nFor this two-class classification problem\, we explored the performances of different modalities such as EEG\, EOG & EMG.  \n\n\nWe also performed ensemble empirical mode decomposition and Poincare plot analysis of the signal for identifying sleep and wake states. \n\n\n\nMulti-class classification of sleep stages using single channel EEG:  \n\n\n\nUtilising the knowledge from earlier works on binary classification\, we considered different sets of features and evaluated the performance of RUSBoost classifier on unseen test subjects. This work reports the performance of different n-class (n=2\,3\,4\,5\,6) classification problems on three publicly available datasets of overnight polysomnography recordings. \n\n\n\nMulti-modal classification of sleep stages using a hierarchical model  \n\n\n\nIn this work\, a six-level hierarchical model (HM) has been designed. The aim is to improve the sleep staging accuracy by breaking down the 5-class classification problem into six binary classification problems\, while also reducing the misclassifications among N1\, REM\, and wake stages.  \n\n\nIntroducing data augmentation (DA) and temporal context (TC) in the proposed hierarchical model to further improve sleep staging performance. We validated the results of DA and TC on healthy as well as clinical populations from seven publicly available datasets. \n\n\n\nDiagnosis of different sleep disorders using a single EEG channel  \n\n\n\nThis work aims to classify seven different sleep disorders and healthy controls using light gradient boosting model with a single-channel EEG.   \n\n\nWe examined the importance of different features in distinguishing various pathological groups and healthy individuals.  \n\n\nWe also evaluated the role of individual sleep stages in distinguishing the different disorders. \n\n\n                                                                                                           ALL ARE WELCOME \nPublications based on this Thesis \n  \nJournals \n1. Ritika Jain and Angarai Ganesan Ramakrishnan. Electrophysiological and neuroimaging studies–during resting state and sensory stimulation in disorders of consciousness: a review. Frontiers Neurosc.\, 14:987\, 2020 \n2. Ritika Jain and Ramakrishnan A G. Reliable sleep staging of unseen subjects with fusion of multiple EEG features and RUSBoost. Biomed. Sig. Proc. Control\, 70:103061\, 2021 \n  \nConferences \n1. Ritika Jain and Ramakrishnan Angarai Ganesan. Assessment of submentalis muscle activity for sleep-wake classification of healthy individuals and patients with sleep disorders. \nIn 44th IEEE EMBC 2022. IEEE\, 2022 \n2. Ritika Jain and Ramakrishnan Angarai Ganesan. Single EOG channel performs well in distinguishing sleep from wake state for both healthy individuals and patients. In 44th \nIEEE EMBC. IEEE\, 2022 \n3. Ritika Jain and Ramakrishnan Angarai Ganesan. Poincar ́e plot analysis for sleep-wake classification of unseen patients using a single EEG channel. In 17th IEEE Int. Symp. \nMed. Meas. Applns. IEEE\, 2022 \n4. Ritika Jain and Ramakrishnan Angarai Ganesan. Classifying sleep-wake states of patients by training on single EEG or EOG channel data from normal subjects. In 2022 IEEE Region 10 Symposium (TENSYMP)\, pages 1–5. IEEE\, 2022 \n5. Ritika Jain and Ramakrishnan Angarai Ganesan. An efficient sleep scoring method using visibility graph and temporal features of single-channel EEG. In 43rd Ann. Int. Conf IEEE EMBC\, pages 6306–6309. IEEE\, 20216. Ramakrishnan A G and Ritika Jain. Binary state prediction of sleep or wakefulness using EEG and EOG features. In 17th India Council Int. Conf (INDICON)\, pages 1–7. IEEE\, 20207. Ritika Jain and Angarai Ganesan Ramakrishnan. Sleep-awake classification using EEG band-power-ratios and complexity measures. In 2020 IEEE 17th India Council International Conference (INDICON)\, pages 1–6. IEEE\, 2020Manuscripts under Review \n  \n• Ritika Jain and Ramakrishnan A G. Modality-specific feature selection\, data augmentation\, and temporal context for superior performance in sleep staging. IEEE Jl. Of Biomedical & Health Informatics\, 2023. \n  \n                                                                 ALL ARE WELCOME – People outside IISc can join through the MS Teams link given.
URL:https://ee.iisc.ac.in/event/ph-d-thesis-colloquium-of-ritika-jain/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230424T160000
DTEND;TZID=Asia/Kolkata:20230424T180000
DTSTAMP:20260404T141033
CREATED:20230423T225041Z
LAST-MODIFIED:20230424T025205Z
UID:240653-1682352000-1682359200@ee.iisc.ac.in
SUMMARY:EE Seminar: High voltage aviation electrical system EMC challenges and opportunities
DESCRIPTION:Dear all\,\n\nI cordially invite you to attend this talk by Dr. Cong Li from GE Aerospace Research\, Niskayuna\, NY\, USA.  The details are given below.\n\nDate & Time: 24/04/2023\, 10.30 am – 11.30 am\n\nVenue: MMCR\, Dept. of Electrical Engineering (Hybrid Mode)\n\nFor online participants:Meeting Link\n\n\n\n\n\nTitle: High voltage aviation electrical system EMC challenges and opportunities\n\n\nAbstract: High voltage aviation electrical systems have unique design challenges to meet ultrahigh power density and reliability requirements under extreme operation conditions. One critical aspect is the Electromagnetic Compatibility (EMC)\, such as emission and susceptibility\, etc. This talk will explain the fundamental EMC challenges for wide band gap (WBG) based high voltage aviation electrical system\, and share an effective “SOLVE” EMC design process for meeting stringent aviation EMC requirements.\n\n\nSpeaker Bio: Dr. Cong Li (S’09-M’15-SM’19) received the Ph.D. degree in electrical engineering specializing in power electronics from The Ohio State University\, Columbus\, OH\, USA\, in 2014. He joined GE Aerospace Research at Niskayuna\, NY\, USA as a Research Engineer in 2014 and is currently a Senior Power Electronics Engineer and EMC Lead. His research interests include aviation high voltage\, high power\, high density wide band gap (WBG) power electronics systems\, and EMI mitigation techniques. He is currently leading multiple flight demo EMC projects at GE Research. He has authored more than dozens of technical papers\, and patent applications in the area of power electronics and EMC. He is a voting member of commercial aviation DO-160 EMI standard working group.\n\nHe has been given EMI webinars and tutorials at multiple IEEE conferences such as ECCE\, APEC\, EMC Symposium\, etc. He is currently a Senior Member of IEEE\, and Associate Editor at IEEE Open Journal of Power Electronics. He is serving as secretary of IEEE-EMCS-SC5 Power Electronics EMC\, as well as Technical Committee member of IEEE APEC\, ECCE\, ITEC\, EATS conferences.\n\n\nRegards\,\nVishnu
URL:https://ee.iisc.ac.in/event/ee-seminar-high-voltage-aviation-electrical-system-emc-challenges-and-opportunities/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230424T203000
DTEND;TZID=Asia/Kolkata:20230424T223000
DTSTAMP:20260404T141033
CREATED:20230423T225448Z
LAST-MODIFIED:20230423T230059Z
UID:240656-1682368200-1682375400@ee.iisc.ac.in
SUMMARY:EE seminar: Advances in Power Electronics and Power Semiconductors for E-mobility Applications
DESCRIPTION:Dear all\, \n\nI cordially invite you to attend this talk by Dr. Ajay Poonjal Pai from Infineon Technologies AG\, Neubiberg\, Germany.  The details are given below.\n\nDate & Time: 24/04/2023\, 3 pm – 4 pm\n\nVenue: B 303 (Old 311)\, Dept. of Electrical Engineering (Hybrid Mode)\n\n\nFor online participants: Meeting Link\n  \nTitle of the Talk: Advances in Power Electronics and Power Semiconductors for E-mobility Applications \n\n\nAbstract: E-mobility has emerged as an interesting application for power electronics and power semiconductors. Not only is this market demonstrating an exponential growth\, but is also filled with interesting challenges. This is where Power semiconductors and power electronics can pitch in to facilitate adoption of electric cars. This talk gives an overview of the most interesting power electronic applications in electric Vehicles\, with a main focus on the traction inverter application\, which is\, by far\, the most important from a power semiconductor point of view. The latest trends in the application and power semiconductor technologies is discussed. Special focus will be given to Silicon Carbide Mosfet technology which offers significant benefits in terms of power density\, switching behaviour\, conduction behaviour etc. Results of power loss measurements are shown and discussed.\n\n\nSpeaker Bio: Dr. Ajay Poonjal Pai obtained his B.Tech in Electrical Engineering from NITK Surathkal\, India and M.Sc. in Electrical Power Engineering from RWTH Aachen University\, Germany. He then pursued his PhD focusing on Silicon Carbide at the Friedrich Alexander University\, Erlangen-Nuremberg\, Germany. Since 2015\, he is working at Infineon Technologies AG\, Neubiberg\, Germany as a Principal Application Engineer responsible for next-generation Silicon Carbide technologies and Power Modules for electric vehicles. His research interests include e-mobility\, Silicon Carbide semiconductors and power electronics. He enjoys following new technologies and understanding trends in the power electronics and automotive markets. He has contributed to several conferences and journals\, and has delivered numerous lectures and tutorials around the world. \n\n\n\n\nRegards\,\nVishnu
URL:https://ee.iisc.ac.in/event/ee-seminar-advances-in-power-electronics-and-power-semiconductors-for-e-mobility-applications/
LOCATION:B 303 (Old 311)\, Dept. of Electrical Engineering (Hybrid Mode)
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230426T163000
DTEND;TZID=Asia/Kolkata:20230426T183000
DTSTAMP:20260404T141033
CREATED:20230425T224859Z
LAST-MODIFIED:20230425T224859Z
UID:240704-1682526600-1682533800@ee.iisc.ac.in
SUMMARY:IISc-TU Delft Talk by Prof Marjan Popov 26th April 11 am
DESCRIPTION:Dear All\, \nProf Marjan Popov of TU Delft will be visiting IISc on 26th April 2023. He will be giving a talk in the MMCR of the Electrical Engineering Department\, from 11 am on “Power System Protection Essentials – research activities”. He will mostly give an overview of the research activity carried out by his lab. This talk is a part of an IISc-TU Delft joint project. \nAll are invited.
URL:https://ee.iisc.ac.in/event/iisc-tu-delft-talk-by-prof-marjan-popov-26th-april-11-am/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230511T153000
DTEND;TZID=Asia/Kolkata:20230511T170000
DTSTAMP:20260404T141033
CREATED:20230510T224334Z
LAST-MODIFIED:20230510T224424Z
UID:240716-1683819000-1683824400@ee.iisc.ac.in
SUMMARY:PhD Oral Examination of Kapil Upamanyu @ 10 am on Thursday\, May 11\, 2023
DESCRIPTION:PhD Oral Examination\n\nName of the candidate: Kapil Upamanyu\nProgramme:                     PhD (Regular)\nDepartment:                    Electrical Engineering\n\nTitle:\nModelling\, Stabilization Methods and Power Amplification for Power Hardware-in-Loop Simulation with Improved Accuracy\n\nSupervisor:                       G Narayanan\n\nDate:                                May 11\, 2023 (Thursday)\nTime:                                10 am – 11:30 am\nVenue:                              Multi-Media Class Room (MMCR)\, EE Department (Hybrid mode)\nVideo link:                       Please find below:\n\nAll are welcome\n\n\n\n\n\n\n\n\nMeeting link \n\n\n\n\n\n\n\n\n\nJoin conversation\nteams.microsoft.com\n\n\n\n\n\n\n  \nThesis title: Modelling\, Stabilization Methods and Power Amplification for Power Hardware-in-Loop Simulation with Improved Accuracy \nAbstract: \n\nSimulations of physical systems are extensively conducted for research and design purpose. Potential of a simulation can be extended significantly by conducting it in real-time. Real-time simulation allows a part of the mathematical model of the system to be replaced by a physical hardware; the real-time simulator (RTS) and the physical hardware interact with each other through sensors and power amplifier (PA). When the operating power level of the PA is considerably higher than that of the sensor signals\, the simulation is called as power hardware in loop (PHIL) simulation. PHIL simulation is a good alternative to the conventional simulation where a part of the system cannot be adequately represented by a mathematical model. Unlike conventional simulation\, PHIL simulation allows the testing of a hardware\, in a safe and controlled environment\, without the rest of the system being available. But several factors\, such as the computation time delay and sampling effects of RTS\, the dynamics of PA and the transport lag of signals\, are part of a PHIL simulation but not that of the actual system. As a result\, the response of the PHIL simulation of a system can differ from that of the actual system. The inaccuracy can be so significant that the PHIL simulation of a system can be unstable even though the actual system is stable\, and vice versa. An unstable PHIL simulation can be stabilized by employing compensation algorithms. This work proposes novel PA for accurate response\, stability analysis methodology for the accurate estimation of instability\, and compensation algorithms for stable response of PHIL simulation. \nConventional switched-mode PAs have limited dynamic response due the presence of passive filter. These PAs employed in a PHIL simulation are unable to accurately replicate the fast transients of the system. An output filter-less voltage source inverter is proposed as a power amplifier suitable to be interfaced with inductive loads (e.g.\, most of the power system loads). Such a PA has a reference tracking bandwidth comparable to the switching frequency. Unlike the output of the conventional PAs\, the output of the proposed PA is completely unaffected by the sudden changes in the current drawn by the loads. The proposed PA is utilized to emulate the transients of synchronous generator\, along with the fast transient corresponding to the field excitation controller\, while feeding a passive linear load. With a proposed improvement in the emulation method\, accurate responses for unbalanced and non-linear loads are also obtained for the emulated generator. With further proposed techniques\, the applicability of the proposed PA is extended for it to be interfaced to PWM converters. The PA is utilized for emulating unbalanced and harmonic (up to 23rd order) grid voltages while testing the control of a PWM rectifier. Accurate current responses are also obtained when the step changes in the grid voltage and the rectifier dc bus reference are considered. \nConventionally\, stability analysis of PHIL simulation is evaluated in continuous-time domain. Since\, a PHIL simulation consists of discrete-time sampling\, a discrete-time domain modelling approach is proposed for more accurate stability analysis. The proposed approach is also used to accurately estimate the stability of a PHIL simulation utilizing compensation algorithms\, such as feedback current filtering method. Novel compensation algorithms\, based on lag compensator and cross coupled compensator\, are proposed for stabilizing those PHIL simulations which cannot be stabilized using existing algorithms. PHIL simulation of a single generator infinite bus power system\, which is originally unstable without and with existing compensation algorithms\, is successfully conducted using the novel cross-coupled compensator. \nPA sourced from a PWM rectifier can be used as 4-quadrant PA. A simple input voltage sensor-less vector control of PWM rectifier is proposed. While the performance of the proposed method\, in terms of THD and power factor\, is comparable to the sensor-based method and existing sensor-less methods\, its computation time requirement is much lower than those for these methods. A discrete-time domain modelling of the PI-controlled current loop of PWM converters is presented. The model is used to derive closed-form time-domain expressions of the current for step changes in the current reference and the disturbance voltage\, for a given set of controller and hardware parameters. Based on the derived expressions\, a pre-filter is proposed to achieve the dead-beat response with the PI-controlled current loop\, while having a disturbance rejection settling time of just ten switching cycles. \nALL ARE WELCOME
URL:https://ee.iisc.ac.in/event/phd-oral-examination-of-kapil-upamanyu-10-am-on-thursday-may-11-2023/
LOCATION:Multi-Media Class Room (MMCR)\, EE Department (Hybrid mode)
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230512T150000
DTEND;TZID=Asia/Kolkata:20230512T180000
DTSTAMP:20260404T141033
CREATED:20230510T231909Z
LAST-MODIFIED:20230510T231909Z
UID:240727-1683903600-1683914400@ee.iisc.ac.in
SUMMARY:[Online] Faculty Candidate Talk Friday 12th May 9:30 am
DESCRIPTION:Dr. Avinash Kumar has applied for a faculty position at the EE Dept IISc. His online talk is scheduled on 12th May 9:30 am. Please find his talk details below. \n \nTopic: Islanding Detection Methods for Inverter Interfaced Distributed Generator (IIDG)\n \n\n\nContinuous disturbance injection-based islanding detection of an inverter-interfaced distributed generator (IIDG) has been a general trend in reported literature work. The major issues that persist in previous islanding detection methods are large Non-Detection Zone (NDZ)\, poor Power Quality (PQ)\, high implementation cost\, and lack of real-time validation. Furthermore\, the selection of a generic threshold is not considered for general applications and depends on the system’s rating. Various types of islanding detection methods are reported in the literature as passive\, active\, and hybrid methods. \nIn this talk\, a local voltage and current measurement-based hybrid islanding detection method for IIDGs will be presented in detail. The parameters are estimated from the fundamental phasors of voltage and current at the Point of Common Coupling (PCC) of IIDG using Space Vector Rotation (SVR). The proposed disturbance in IIDG is injected only after disturbance detection by SVR parameters to mitigate the impact on PQ. Disturbance identification is easy due to the combined PCC voltage and current effects on parameter estimation. The disturbance injection is controlled and self-decaying. Further\, the talk will discuss the validation of the proposed approach on Real-Time Digital Simulator (RTDS) and Controller Hardware In the Loop (CHIL) setup. The talk will also highlight the advantage of the proposed method in terms of real-time efficacy (low islanding detection time) with no NDZ and negligible impact on PQ for the detection of different islanding events. \nAt the end of the talk\, a brief overview of recently reported work on “Dynamic-State-Estimation-Based Cyber Attack Detection for Inverter-Based Resources” will be delivered. \n\nThe link of the talk is: \n\nTeam Link
URL:https://ee.iisc.ac.in/event/online-faculty-candidate-talk-friday-12th-may-930-am-2/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230515T163000
DTEND;TZID=Asia/Kolkata:20230515T163000
DTSTAMP:20260404T141033
CREATED:20230510T225124Z
LAST-MODIFIED:20230510T230029Z
UID:240720-1684168200-1684168200@ee.iisc.ac.in
SUMMARY:Ph. D. Thesis Colloquium of Mr. Pradeep K. G.: 11 am Monday\, 15 May: EEG correlates of non-ordinary states of consciousness and slow-paced breathing
DESCRIPTION:  \nTitle: EEG correlates of non-ordinary states of consciousness and slow-paced breathing  \n\n\nName of the student: Pradeep Kumar G  \n\n\nAdvisor: Prof.  A. G. Ramakrishnan  \n\n\nDate and Time: 15 May 2023 (Monday) 11:00 AM  \n\n\nVenue: Hybrid: MMCR\, Hall C 241\, 1st floor\, Department of EE  \nMeeting Link  \n  \n\n\n==================================================================================  \n\n\nTITLE: EEG correlates of non-ordinary states of consciousness and slow-paced breathing  \n\n\nStudies on the non-ordinary states of consciousness (NSCs) induced by meditation\, hypnosis\, and trance are gaining visibility due to their potential efficacy in treating various clinical conditions. Slow-paced breathing at six cycles per minute (cpm) has been labelled as coherent breathing since it has been suggested to induce synchronous resonance frequency in various physiological signals. These self-regulatory or guided processes are practiced primarily to reduce stress and manage emotions and mental health. However\, the underlying mechanisms for the health benefits of these practices still need to be fully understood. Electroencephalography (EEG)\, a non-invasive electrophysiological tool to investigate brain’s electrical activity\, is used to study the changes in brain dynamics during different NSCs.  \n\n\n\n  \n\n\nSignificant contributions of the thesis:  \n\n\n\nChanges in EEG coupling during eyes-open meditation.  \n\n\n\n\nThe interdependencies between brain signals clustered in different groups across the hemispheres were studied using bivariate functional connectivity (FC) methods.  \n\n\nChanges in the FC between EEG electrode pairs were investigated during the meditation practiced by long-term Brahmakumaris Rajyoga meditators with open eyes and during listening to music by controls as the comparable task.  \n\n\n\n\n\n\nCommon and distinct patterns were observed in distinct frequency bands in meditators and control groups. Node-degree strength was consistently higher in meditators than controls in theta band.  \n\n\n\n  \n\n\n\nSynergy and redundancy of the brain during different non-ordinary states of consciousness.  \n\n\n\n\nThis is a multicentric study on three different NSCs: Rajyoga meditation (RM)\, hypnosis\, and self-induced cognitive trance (SICT).  \n\n\nSynergistic and redundant information measures were used to compare and contrast the higher-order interactions during three NSCs.  \n\n\n\n\n\n\nThe synergy of the brain increased during RM and decreased during hypnosis and SICT\, and redundancy decreased during RM.  \n\n\nThe pattern of changes observed in the synergy and redundancy values of each NSC is defined by the phenomenology of the NSC\, including changes in the sense of self\, environmental awareness\, altered sensory perception\, and selective attention.  \n\n\n\n   \n\n\n\nRespiration-entrained brain oscillations during slow-paced breathing.  \n\n\n\n\nCoherence between the cortical activity (EEG) and respiration were analyzed during baseline and slow-paced breathing at six cpm guided by visual metronome.  \n\n\n\n\n\n\nSignificant coherence between respiration and EEG was observed\, with no common localization across subjects. However\, the coherence further increased during the slow-paced breathing at six cpm.  \n\n\nPhase-amplitude coupling showed distinct patterns during baseline and slow-paced breathing in specific EEG frequency bands.  \n\n\nThe modulation index increased during slow-paced breathing compared to baseline\, supporting the link between respiration and brain activity and providing possible insight into the benefits of therapeutic breathing exercises like pranayama.  \n\n\n\n  \n\n\n——————           ALL ARE WELCOME               —————
URL:https://ee.iisc.ac.in/event/ph-d-thesis-colloquium-of-mr-pradeep-k-g-11-am-monday-15-may-eeg-correlates-of-non-ordinary-states-of-consciousness-and-slow-paced-breathing/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230522T133000
DTEND;TZID=Asia/Kolkata:20230527T223000
DTSTAMP:20260404T141034
CREATED:20230519T005801Z
LAST-MODIFIED:20230519T041948Z
UID:240749-1684762200-1685226600@ee.iisc.ac.in
SUMMARY:Research Admission 2023
DESCRIPTION:Info_EE_ResInterview_2023\nChoice of research areas of 2023\n\nEateries:- Click here(Nesara)\, Click here (Sarvam)
URL:https://ee.iisc.ac.in/event/research-admission-2023/
LOCATION:EE\, IISc
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230620T080000
DTEND;TZID=Asia/Kolkata:20230707T170000
DTSTAMP:20260404T141034
CREATED:20230703T083659Z
LAST-MODIFIED:20230703T084023Z
UID:240793-1687248000-1688749200@ee.iisc.ac.in
SUMMARY:Summer School 2023
DESCRIPTION:Summer School 2023 Website Link \nsummer school | EE (iisc.ac.in)
URL:https://ee.iisc.ac.in/event/summer-school-2023/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230621T160000
DTEND;TZID=Asia/Kolkata:20230621T183000
DTSTAMP:20260404T141034
CREATED:20230619T035749Z
LAST-MODIFIED:20230619T035749Z
UID:240776-1687363200-1687372200@ee.iisc.ac.in
SUMMARY:Ph. D. Colloquium - Ms. Anwesha Mukhopadhyay: 10.30 am Wed\, 21 June 2023: Reduced Electrolytic Capacitor-Based Single-Phase Converters: Topologies\, Control\, and Stability
DESCRIPTION:Ph. D. Thesis ColloquiumStudent: Anwesha MukhopadhyayAdvisor: Prof. Vinod JohnDegree: PhDDate and Time: 10:30 AM\, 21st June 2023Place: MMCR EE\, IISc.=======================================================Title: Reduced Electrolytic Capacitor-Based Single-Phase Converters: Topologies\, Control\, and StabilityAbstract: Single-phase power converters find wide applications as inverters for grid integration of solar photovoltaics\, fuel cells\, front-end converters for consumer electronics\, battery chargers for electric vehicles\, etc. Applications ranging from a few hundred Watts for household solar micro-inverters\, to multi-Megawatt levels for electric traction powertrain\, single-phase converters are adopted worldwide.In single-phase power conversion\, there is always a mismatch between the instantaneous input and output power\, producing a second-harmonic ripple in the dc link current. Electrolytic capacitors are conventionally deployed for filtering the second-harmonic ripple due to their low cost and excellent energy density. However\, their frequent premature failures often compromise the lifespan of the converters. Therefore\, in applications demanding higher reliability\, electrolytic capacitors are minimised or eliminated completely. In recent technologies demanding high power density\, active filters have minimised the electrolytic capacitors in the circuit. However\, the cost\, efficiency\, and power density trade-offs need scrutiny before adopting an active filter topology.Among the reported active filters (AF) for second-harmonic ripple mitigation\, series capacitor stacked buffer (SSB) topology has emerged as a popular choice owing to its high efficiency and compactness. The use of low VA-rated switching devices enables achieving the high efficiency equivalent to passive filters. Owing to these benefits\, the use of SSB is proposed in two-terminal active capacitors and active inductors and pulsed power applications.Despite its prospective utility in a range of applications\, the model of the SSB\, essential for implementing functional engineering control strategies under a wide range of operating conditions\, is not discussed in existing literature. In the first part of the work\, the plant model for controlling the buffer converter in voltage control mode as well as current control mode is developed. Using the proposed model\, a closed-loop control scheme is developed\, which ensures a fixed-frequency switching of the buffer converter. A step-by-step controller design procedure is elaborated\, and the controller gain limit is identified to ensure closed-loop stability. The stability limit and the filtering performance are verified experimentally on a hardware prototype.Based on the developed SSB model\, an average current mode control is implemented in the second part of the work. Unlike the existing methods of current mode control\, in the proposed scheme\, the current reference is estimated without using the dc-link current sensor\, which is verified experimentally.The SSB-based existing topologies\, though promising for many applications\, are not realised with minimum switch counts. As opposed to four switch H-bridge-based buffer converter\, two switch-based series capacitor stacked buffer converter topologies are synthesised in this part of the work. The generalised topology synthesis procedure and control challenges are identified. One of the proposed two-switch-based topologies named Series Capacitor Boost Hybrid Filter (SC-BOHF) is implemented and verified experimentally.Apart from the active solutions\, an alternative dc bus filter structure\, consisting of a combination of an inductor (L) and capacitor (C)\, tuned at the second harmonic (2ω) frequency\, reduces the capacitance requirement\, enhancing the likelihood of deployment of film capacitors. The proposed solid-state tuning restorer (SSTR) offers consistent filtering performance of the LC filter under frequency and parameter variations. As per the tuning requirement of the LC filter\, SSTR acts as an electronic inductor or capacitor. It also ensures a graceful degradation in the filter characteristics during SSTR converter failure modes. The evolution of the SSTR configuration\, analysis of its VA rating\, and control requirements are studied in this work.The realisation that SSTR requires to behave as an electronic inductor and capacitor as per the sense of LC filter detuning motivated this part of the work\, where a unified active capacitor and inductor (UACI) is proposed and implemented without using any dc capacitor. Conventionally\, an H-bridge-based active capacitor or inductor requires large dc capacitances to ensure satisfactory current THD. In the proposed configuration\, a dc capacitor-less three-leg converter topology is proposed to emulate a two-terminal unified active capacitor and inductor. Based on the current reference\, the proposed configuration emulates inductive or capacitive characteristics and smoothly transits from one characteristic to another. The operation of the proposed UACI is studied\, and a closed-loop control scheme is developed.All the proposed methods are validated on hardware prototypes that have been developed as a part of the work.              ——————           ALL ARE WELCOME               —————
URL:https://ee.iisc.ac.in/event/ph-d-colloquium-ms-anwesha-mukhopadhyay-10-30-am-wed-21-june-2023-reduced-electrolytic-capacitor-based-single-phase-converters-topologies-control-and-stability/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230621T163000
DTEND;TZID=Asia/Kolkata:20230706T223000
DTSTAMP:20260404T141034
CREATED:20230612T003521Z
LAST-MODIFIED:20230718T050519Z
UID:240769-1687365000-1688682600@ee.iisc.ac.in
SUMMARY:Provisional Research Admission Results 2023
DESCRIPTION:Provisional research admission results 2023 \nProvisinal Result reserch 2023 \n 
URL:https://ee.iisc.ac.in/event/provisional-research-admission-results-2023/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230626T163000
DTEND;TZID=Asia/Kolkata:20230626T183000
DTSTAMP:20260404T141034
CREATED:20230619T055437Z
LAST-MODIFIED:20230619T055437Z
UID:240778-1687797000-1687804200@ee.iisc.ac.in
SUMMARY:[CPRI Chair Talk] Prof Sukumar Brahma on 26th June 2023 at 11 am at MMCR\, EE Dept
DESCRIPTION:——————————————————————————————————– \nTitle: Source-Agnostic\, Inherently Directional Time-Domain Distance Relay \n——————————————————————————————————– \n\nAbstract: \nThere have been reported instances of legacy numerical distance relays failing to identify fault direction when they are fed by an inverter based resource (IBR) – solar\, wind or storage. This is largely because the response to fault from an inverter is radically different than the fault response of a traditional synchronous machine. This presentation will explain the reasons for misoperations and introduce design\, implementation\, testing and validation of a distance relay designed in time domain which avoids polarization problems in numerical legacy relays that operate in phasor domain. It will also report superior performance of the proposed relay when compared to the only time-domain distance relay in the market that operates based on travelling waves. \n\nBio: \nSukumar Brahma received his Bachelor of Engineering from Gujarat University in 1989\, Master of Technology from Indian Institute of Technology\, Bombay in 1997\, and PhD in from Clemson University in 2003; all in Electrical Engineering. He joined Clemson university as the Dominion Energy Distinguished Professor of Power Engineering in August 2018. He also serves as the director of the industry-funded Clemson University Electric Power Research Association (CUEPRA). Before joining Clemson he was William Kersting Endowed Chair Professor at New Mexico State University\, USA. Dr. Brahma has chaired IEEE Power and Energy Society’s Power and Energy Education Committee\, Life Long Learning Subcommittee and Distribution System Analysis Subcommittee. He is a member of the Power System Relaying and Control Committee (PSRCC)\, where he has been contributing to and leading working groups that produce reports\, guides and standards in the area of power system protection. He has been an editor for IEEE Transactions on Power Delivery\, and served as Guest Editor-in-Chief for the Special Issue on Frontiers of Power System Protection for the journal. His research\, widely published and funded by the National Science Foundation\, US Department of Energy\, utilities\, and other government agencies has focused on different aspects of power system modeling\, analysis\, and protection. Fundamentally\, it spans across diverse areas of electrical engineering and computer science\, integrating signal processing\, machine learning\, control and communication to holistically approach the emerging problems in the power and energy domain. Current research\, funded by the US Department of Energy\, investigates and addresses protection and fault location issues in integration of renewables with power systems and develops new paradigms in protection of smart grid\, at both transmission and distribution levels. \n\nDr. Brahma is a Distinguished Lecturer of the IEEE and CPRI Visiting Chair Professor at IISC in 2022-23. He has been elected IEEE Fellow “for contributions to power system protection with distributed and renewable generation”.
URL:https://ee.iisc.ac.in/event/cpri-chair-talk-prof-sukumar-brahma-on-26th-june-2023-at-11-am-at-mmcr-ee-dept/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230630T110000
DTEND;TZID=Asia/Kolkata:20230630T130000
DTSTAMP:20260404T141034
CREATED:20230626T033835Z
LAST-MODIFIED:20230626T033835Z
UID:240780-1688122800-1688130000@ee.iisc.ac.in
SUMMARY:[EE Seminar] - Prof. Saikat Chatterjee\, KTH - {Data-driven Non-linear State Estimation of Model-free Process in Unsupervised Learning}\, Friday\, June 30th\, 11am\, MMCR\, EE.
DESCRIPTION:The IEEE Signal Processing Society\, Bangalore Chapter\, and the Electrical Engineering\, IISc are happy to host the following talk\,\n \nVenue : MMCR (C241)\, EE\, IISc\nTime : 11am-12noon\nDate : 30-June-2023\nSpeaker : Prof. Saikat Chatterjee (KTH)\n \n================\n\nTitle:        DANSE: Data-driven Non-linear State Estimation of Model-free Process in Unsupervised Learning Setup\nAbstract:\nWe address the tasks of Bayesian state estimation and forecasting for a model-free process in an unsupervised learning setup. In the seminar\, we discuss our new method called DANSE – Data-driven Nonlinear State Estimation method. DANSE provides a closed-form posterior of the state of the model- free process\, given linear measurements of the state. In addition it provides a closed-form posterior for forecasting. We show how data-driven recurrent neural networks (RNNs) are used in the DANSE to provide closed-form prior of the state and posterior. The training of DANSE\, mainly learning the parameters of RNN\, is executed in an unsupervised learning approach. In unsupervised learning\, we have access to a training dataset consisting of only a set of measurement data trajectories\, but we do not have any access to the state trajectories. Therefore\, DANSE does not have access to state information in training data and can not use supervised learning. Using simulated linear and non- linear process models (Lorenz attractor and Chen attractor)\, we evaluate the unsupervised learning- based DANSE. We show that the proposed DANSE\, without knowledge of the process model and without supervised learning\, provides a competitive performance against model-driven methods\, such as Kalman filter (KF)\, extended KF (EKF) and unscented KF (UKF)\, and a recently proposed hybrid method called KalmanNet.\nPreprint of the paper: https://arxiv.org/abs/2306.03897\nBio:\nSaikat Chatterjee is associate professor at School of Electrical Engineering and Computer Science\, KTH-Royal Institute of Technology\, Sweden. He received a Ph.D. degree from Indian Institute of Science\, India. His website: https://www.kth.se/profile/sach\n\n=================\n\n\n\n​All are welcome\,
URL:https://ee.iisc.ac.in/event/ee-seminar-prof-saikat-chatterjee-kth-data-driven-non-linear-state-estimation-of-model-free-process-in-unsupervised-learning-friday-june-30th-11am-mmcr-ee/
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Kolkata:20230710T150000
DTEND;TZID=Asia/Kolkata:20230710T170000
DTSTAMP:20260404T141034
CREATED:20230710T034621Z
LAST-MODIFIED:20230710T034621Z
UID:240823-1689001200-1689008400@ee.iisc.ac.in
SUMMARY:IEEE PES Talk: Prof. Satyajayant Misra\, 10-07-2023\, Monday 3PM - 4PM\, MMCR\, EE
DESCRIPTION:Title: An Information-Centric Network Architecture for DDoS Protection in the Smart Grid \n\n\n\nTime and Time: 3 PM – 4 PM\, Monday\, 10 July 2023 \n\nVenue:  MMCR\, EE\, IISc \n\n\n\n\n\nAbstract: With the proliferation of differently-abled and heterogeneous devices in the smart grid Denial of Service (DoS) is becoming an even more potent attack vector than it was before. We demonstrate the ease with which an adversary can orchestrate DoS and distributed DoS (DDoS) attacks on the grid. In this talk\, we will discuss our proposed architecture iCAD–an information-centric network architecture\, and our prior architecture iCAAP\, on which iCAD is built. We discuss our architecture in detail and demonstrate the architecture and the mitigation technique’s effectiveness in mitigating significant DoS/DDoS attacks. \n\n\n\n\n \nBio: Dr. Satyajayant Misra (Jay) is a professor of computer science and electrical and computer engineering at New Mexico State University (NMSU). He is also the associate dean of research for the College of Engineering. His research expertise is in cybersecurity and computer networking and his recent research interests are in edge computing\, future Internet\, the smart grid\, cryptocurrencies\, and decentralized finance. He has over 100 peer-reviewed publications in several prestigious venues\, such as ACM CCS\, IEEE/ACM Transactions on Networking and Mobile Computing\, IEEE/ACM Supercomputing Conference\, and IEEE Transactions on Intelligent Transportation Systems. His research has garnered over 7700 international citations and he has an h-index of 26 and an i-10 index of 60. His research has been supported by Intel Labs\, US NSF\, DoD\, DoE\, DoEd\, and the FAA\, and national labs such as Sandia National Lab\, LANL\, and Idaho National Lab.
URL:https://ee.iisc.ac.in/event/ieee-pes-talk-prof-satyajayant-misra-10-07-2023-monday-3pm-4pm-mmcr-ee/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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DTSTART;TZID=Asia/Kolkata:20230711T150000
DTEND;TZID=Asia/Kolkata:20230711T170000
DTSTAMP:20260404T141034
CREATED:20230704T112914Z
LAST-MODIFIED:20230704T112914Z
UID:240799-1689087600-1689094800@ee.iisc.ac.in
SUMMARY:M.Tech.(Res.) Thesis Defense of Vishwabandhu Uttam
DESCRIPTION:Title: A Unified Modeling Approach for Design and Performance Improvement of Triple Active Bridge Converter\nName of the Student: VISHWABANDHU UTTAM\,  M.Tech (Res) in Electrical Engineering\n\nResearch Supervisor: Vishnu Mahadeva Iyer\nExternal Examiner: Anirudh Guha\, Assistant Professor\, IIT Palakkad\n\nDate/Time: 11th July 2023\, Tuesday at 3:00 PM\nLocation: MMCR (Electrical Engineering)\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.\nThe popular First 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.\n\nWe request your presence at the thesis defense.\nAll are welcome.
URL:https://ee.iisc.ac.in/event/m-tech-res-thesis-defense-of-vishwabandhu-uttam/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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DTSTART;TZID=Asia/Kolkata:20230712T110000
DTEND;TZID=Asia/Kolkata:20230712T130000
DTSTAMP:20260404T141034
CREATED:20230711T065544Z
LAST-MODIFIED:20230711T065729Z
UID:240829-1689159600-1689166800@ee.iisc.ac.in
SUMMARY:[Oral Examination Talk] - A Learnable Distillation Approach For Model-agnostic Explainability With Multimodal Applications\, {Debarpan\, EE} [MMCR\, EE\, 11:00AM\, July 12]
DESCRIPTION:Title: A Learnable Distillation Approach For Model-agnostic Explainability With Multimodal Applications \nVenue: MMCR\, C241\, EE\, IISc\, and also in the Teams Link\n\n\nDate and Time: July 12\, 11:00AM.\n\n\n\nSpeaker: ​ Debarpan Bhattacharya\, MTech (Res) EE\, IISc\n\n\nAbstract: \nDeep 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 generates the output decisions. \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. This 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.  \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/ViT 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\n\n  \n​\n—————\n\nAll are welcome
URL:https://ee.iisc.ac.in/event/oral-examination-talk-a-learnable-distillation-approach-for-model-agnostic-explainability-with-multimodal-applications-debarpan-ee-mmcr-ee-1100am-july-12/
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DTSTART;TZID=Asia/Kolkata:20230714T110000
DTEND;TZID=Asia/Kolkata:20230714T130000
DTSTAMP:20260404T141034
CREATED:20230710T034816Z
LAST-MODIFIED:20230710T034816Z
UID:240825-1689332400-1689339600@ee.iisc.ac.in
SUMMARY:[PhD Colloquium of Akshara Soman\, EE on 14/7\, 11AM] {Investigating Neural Encoding of Word Learning and Speech Perception}
DESCRIPTION:Dear All\,\nInviting you to the PhD Thesis Colloquium talk with the following details. \n \n—-\nSpeaker: Ms. Akshara Soman\n\n\n\n\nTitle: Investigating Neural Encoding of Word Learning and Speech Perception\n\nDate & Time : 14-7-2023\, 11:00AM\nVenue : MMCR (C241)\, EE\, IISc\n\nResearch Supervisor: Prof. Sriram Ganapathy\, EE.\n \n=================================================================ABSTRACT\nLanguage learning and speech perception are remarkable feats performed by the human brain\, involving complex neural mechanisms that allow us to understand and communicate with one another. Unravelling the mysteries of these mechanisms has far-reaching implications\, from theories of human cognition to developing effective language learning strategies and advancing speech technology. By employing a multidisciplinary approach encompassing neural investigations using EEG signals\, behavioral analyses\, and machine learning perspectives\, this talk sheds light on the underlying processes involved in word learning and speech perception.\n\nThe talk is divided into three parts. The first part begins by examining how an imitation based learning of foreign sounds is captured in the EEG signals. In this listen and reproduce setting\, subjects were introduced to words from a foreign language (Japanese)\, and English. The subjects were also asked to articulate the words. The results show that time-frequency features and phase in the EEG signal contain information for language discrimination. Further analysis showed that speech production improved over time\, and the frontal brain regions were involved in language learning. These findings suggest the potential of EEG for personalized language exercises and for assessing learners’ abilities.\n\nThe next part of the talk investigates how learning patterns change when semantics are introduced and presented in a sentence context. The participants listen to Japanese words in an English sentence\, once before understanding the semantics of these words and later with the semantic exposure. We quantify the learning patterns in the EEG signal. Notably\, a delayed P600 component emerges for Japanese words\, suggesting short-term memory processing unlike the N400 typically seen for incongruent words in the known language. The brain regions associated with semantic learning are also identified in this study using the EEG data.\n\nIn the final part of the talk\, we analyze the neural mechanisms of human speech comprehension using a match-mismatch classification of the continuous speech stimulus and the neural response (EEG). We make three major contributions on this front –  i) Illustrate the role of word-boundaries in continuous speech comprehension for the first time\, ii) Elicit the encoding of speech data (acoustics) as well as the text data (semantics) in the EEG signal\, and\, iii) Increased signature of semantic content (text) in the EEG data in acoustically challenging environments of dichotic listening.  The findings have potential applications for understanding speech recognition in noise\, brain-computer interfaces\, and attention studies.\n\nIn summary\, the talk will attempt to enhance our understanding of language learning\, speech comprehension\, and the neural mechanisms involved.\n===========================================================\n\n\nALL ARE WELCOME\n\n\n\n\n\n\n—-
URL:https://ee.iisc.ac.in/event/phd-colloquium-of-akshara-soman-ee-on-14-7-11am-investigating-neural-encoding-of-word-learning-and-speech-perception/
LOCATION:MMCR\, Hall C 241\, 1st floor\, EE department
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