Announcements:
Current -
Top 4 of the course - 1. Ranvijay Singh, 2. Sobhan Kanti Dhara, 3. Pranav Shukla, 4. Dibbendu Roy.
Past -
All announcements will be made only in usebackpack.com (https://www.usebackpack.com/iitkgp/courses/9b2ec0).
July 20: Usebackpack.com will be used to share many resources including lecture slides. It will be also used for coding assignment submissions. So it is important that you register yourself at the course page available in usebackpack.com with the alphanumeric code given in today's lecture (first lecture).
Course Objective:
The course will cover advanced digital signal processing topics mainly targeted at applications such as image and video signal processing. Some basic signal processing concepts will be touched upon as well. An important component of the course will be a project in an application domain.
Reference Books & Resources:
- Digital Signal Processing: Principles, Algorithms and Applications by John G. Proakis, Dimitris G. Manolakis
- Signals and Systems by Alan V. Oppenheim and Alan S. Willsky
- Discrete-Time Signal Processing by Alan V. Oppenheim and Ronald W. Schafer
- Wavelet Transforms: Introduction to Theory and Applications by Raghuveer M. Rao and Ajit S. Bopardikar
- Probability, Random Variables and Stochastic Processes by Athanasios Papoulis and S. Unnikrishna Pillai
- Fundamentals of Nonlinear Digital Filtering by Jaakko Astola and Pauli Kuosmanen
- Nonlinear Digital Filters by Ioannis Pitas and Anastasios N. Venetsanopoulos
- Fundamentals of Digital Image Processing by Anil K. Jain
- Digital Image Processing by William K. Pratt
- Digital Image Processing by R. Gonzalez and R. Woods
- The Essential Guide to Video Processing by Alan C. Bovik
- Video Processing and Communications by Yao Wang, Jörn Ostermann, and Ya-Qin Zhang
- Color Image Processing and Applications by Konstantinos N. Plataniotis and Anastasios N. Venetsanopoulos
& Research Papers
Information:
Class Timings - Monday 11.30 - 12.25 HRS, Tuesday 09.30 - 11.25 HRS and Thursday 07.30 to 08.25 HRS
Venue - F-102, Electronics & Electrical Communication Engineering Building.
Office hours - Tuesday – 4.45 to 5.45pm and Thursday – 9 to 10am
Course Syllabus & Evaluation:
As this is an advanced technology course, the syllabus will be kept fluid. A tentative syllabus has been uploaded in usebackpack.com. A term project, multiple open book assignments, coding assignments, mid-term exam and end-term exam will be used to evaluate performance in this course. Details of the evaluation is available in usebackpack.com (https://www.usebackpack.com/iitkgp/courses/9b2ec0).
Lecture Resources: (will be posted in usebackpack.com after the lecture is done)
Usebackpack Link: https://www.usebackpack.com/iitkgp/courses/9b2ec0
Lecture 1 (July 20): Discrete Signals
Lectures 2 & 3 (July 21): Discrete Systems
Tutorial 1 (July 24): Open Assignment 1
Lecture 4 (July 27): Z-transform
Lectures 5 & 6 (July 28): Z-transform
Tutorial 2 (July 30): Open Assignment 2
Lecture 7 (August 03): Frequency Analysis of Discrete Time Signals and Systems
Lectures 8 & 9 (August 04): Frequency Analysis of Discrete Time Signals and Systems
Tutorial 3 (August 06): Open Assignment 3
Lecture 10 (August 10): Discrete Fourier Transform
Lectures 11 & 12 (August 11): Discrete Fourier Transform
Tutorial 4 (August 13): Open Assignment 4
Lecture 13 (August 17): Signal Transforms
Demo 1 (August 20): Demonstration of 2D DCT
Lecture 14 (August 24): Signal Transforms
Lectures 15 & 16 (August 25): Sampling and Reconstruction
Lecture 17 (August 27): Multirate DSP
Tutorial 5 (September 07): Mock Mid-sem Exam
Lectures 18 & 19 (September 08): Multirate DSP and Applications
Lecture 20 (September 24): Gaussian & Gabor Filters and Pyramids
Lecture 21 (September 28): Wavelets
Lectures 22 & 23 (September 29): Wavelets
Lecture 24 (October 01): Wavelets
Lecture 25 (October 05): Wavelets: Applications
Lectures 26 & 27 (October 06): Wavelets: Applications
Lecture 28 (October 08): Random Signal Processing
Lecture 29 (October 12): Random Signal Processing
Lectures 30 & 31 (October 13): Random Signal Processing
Lecture 32 (October 15): KL Transform
Lecture 33 (October 26): Nonlinear Signal Processing /Filtering
Lecture 34 & 35 (October 27): Nonlinear Signal Processing /Filtering
Lecture 36 (October 29): Nonlinear Signal Processing /Filtering
Lecture 37 (November 02): Nonlinear Signal Processing /Filtering
Lecture 38 & 39 (November 03): Nonlinear Filtering, Wiener Filter
Lecture 40 (November 05): Kalman Filter
Lecture 41 (November 09): Filtering Applications
Lecture 42 & 43 (November 10): Filtering Applications
Tutorial 6 (September 16): Mock End-sem Exam