Instructor:
Shayan G. Srinivasa,
[Tuesday, Thursday 11:30 am – 1:00 pm]
Pre-requisities:
Undergraduate Signals and Systems, Digital Signal Processing, Some background in linear algebra and probability
Course Syllabus:
- Introduction to probability and random processes: basic definitions, discrete, continuous and mixed random variables, probability density function, cumulative density function, various notions of stationarity, ergodicity, filtering noise through linear systems, Signal spaces and signal geometry,
- Topics in sampling: Shannon sampling theorem for bandlimited and random signals, basic ideas on compressive sampling,
- Sampling rate conversion: decimation, expansion and rational fractional rate conversion, filter banks and applications.
- Introduction to transform methods: Fourier transforms and convergence issues, wavelets and algorithms for fast decomposition.
Reference Books:
- Moon & Stirling, Mathematical Methods and Algorithms for Signal Processing, Prentice Hall, 2000.
- P. P. Vaidyanathan, Multirate systems and filterbanks, Prentice Hall Signal Processing Series
- Lecture notes
Grading Policy:
- Homeworks : 25%
- Mid Term Exams : 25%
- Project : 25%
- Final Exam : 25%
Homeworks:
Exams:
Project:
Announcements:
Midterm-2: Saturday, 7th April, 2PM – 5PM
Final Exam: Thursday, 26th April, Forenoon (As per IISc schedule)
Mini Project:
Title and Abstract: Tuesday 27th March
Report Submission: Tuesday 22nd April (tentative)
Project Presentations: 30th April