E9 201 (AUG) 3:0 Digital Signal Processing



Digital Signal Processing
August-December, 2020

Announcements:
 		October 1, 2020: First lecture will be held on 6th OCT 2020 (Tuesday) at 3:30 pm.
October 1, 2020: If you are attending the course (credit or audit), please fill up this form (on or before October 13, 2020) to join the class email list.
Instructor:
 		Soma Biswas
Office: EE C 320
Phone: +91 (80) 2293 3538
somabiswas AT iisc.ac.in


Prasanta Kumar Ghosh
Office: EE C 330
Phone: +91 (80) 2293 2694
prasantg AT iisc.ac.in
Teaching Assistant(s):
    TBA


Class meetings:
 		3:30pm to 5:00pm every Tuesday and Thursday (Venue)
Course Group:
 		Use Microsoft Teams Code 8rca1s1 to join the course group.


Modes of instruction
  • Class Materials (Slide pdf) will be uploaded in Teams and course webpage at least one day before the class.
  • Students are strongly encouraged to go through the slides once before the class.
  • The classes will be recorded, so that you can go over them again if required.
  • Continuous evaluation (Surprise Tests) will be carried out in several classes, based on the previously covered materials - so you should always be well prepared.


Course Content:
  • Discrete time signals and systems
  • Z -transform
  • Sampling
  • Discrete Fourier transform, FFT
  • Fourier analysis of signal using DFT
  • Structures of DT system, Quantization effect on DT system structure
  • Bandpass sampling, Multi-rate signal processing
  • Transform analysis
  • Filter design
  • Parametric Signal model
  • Discrete hilbert transform


Prerequisites:

Textbooks:
  • Proakis and Manolakis, Digital Signal Processing, PHI.
  • Discrete-Time Signal Processing by Alan V Oppenheim and Ronald W Schafer, Pearson; 3 edition (18 August 2009)


Web Links:
 		Multirate Digital Filters, Filter Banks, Polyphase Networks, and Applications: A Tutorial
Sampling signals with finite rate of innovation
The Shannon Sampling Theorem-Its Various Extensions and Applications: A Tutorial Review
Multi-channel sampling of low-pass signals
Thinking About Thinking: The Discovery of the LMS Algorithm
Adaptive Noise Cancelling: Principles and Applications
Grading:
  • Assignments (20 points) - 6 assignments. Average of all assignments will be considered. Assignments are meant for learning and preparation for exams. Students may discuss homework problems among themselves but each student must do his or her own work. Cheating or violating academic integrity (see below) will result in failing in the course. Turning in identical homework sets counts as cheating.
  • Surprise Test (30 points) - A total of 15-20 in-class surprise tests (each 3 points) will be conducted and the best 10 will be considered.
  • Midterm exam. (10 points) - 2 midterm exams will be conducted and average of the two will be taken. Missed exams earn 0 points. No make-up exams.
  • Final exam. (20 points)
  • Project (20 points) - Quality of work (5 points), Quantity of work (5 points), Report (5 points), Presentation (5 points).
Topics covered:
Date
Topics
 Remarks
Oct 6
Course logistics
 Introductory lecture
Oct 8
Different types of signals, examples, concept of frequency, relation between frequency of discrete-time and continuous-time sinusoid, sampling theorem.
Notes
List of topics covered date-wise are now available/updated in the Microsoft Teams.









Academic Honesty:
 		As students of IISc, we expect you to adhere to the highest standards of academic honesty and integrity.
Please read the IISc academic integrity.