Course Name: Fundamentals of Wavelets, Filter Banks and Time Frequency Analysis

Course abstract

The word ‘Wavelet’ refers to a little wave. Wavelets are functions designed to be considerably localized in both time and frequency domains. There are many practical situations in which one needs to analyze the signal simultaneously in both the time and frequency domains, for example, in audio processing, image enhancement, analysis and processing, geophysics and in biomedical engineering. Such analysis requires the engineer and researcher to deal with such functions that have an inherent ability to localize as much as possible in the two domains simultaneously.This poses a fundamental challenge because such a simultaneous localization is ultimately restricted by the uncertainty principle for signal processing. Wavelet transforms have recently gained popularity in those fields where Fourier analysis has been traditionally used because of the property, which enables them to capture local signal behavior. The whole idea of wavelets manifests itself differently in many different disciplines, although the basic principles remain the same. Aim of the course is to introduce the idea of wavelets, filter banks and time-frequency analysis. Haar wavelets have been introduced as an important tool in the analysis of signal at various level of resolution. Keeping this goal in mind, idea of representing a general finite energy signal by a piecewise constant representation is developed. Concept of ladder of subspaces, in particular the notion of ‘approximation’ and ‘Incremental’ subspaces is introduced. Connection between wavelet analysis and Multirate digital systems have been emphasized, which brings us to the need of establishing equivalence of sequences and finite energy signals and this goal is achieved by the application of basic ideas from linear algebra. Then the relation between wavelets and Multirate filter banks, from the point of view of implementation is explained.


Course Instructor

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Prof. V.M.Gadre

Prof. Vikram M. Gadre is currently a Professor at Department of Electrical Engineering, IIT Bombay. He received his Undergraduate degree, along with President’s Gold Medal for cumulative performance during his B.Tech, from IIT Delhi in 1989. He received his PhD degree in Electrical Engineering from Indian Institute of Technology, Delhi in 1994.His research interests are Communication and signal processing, with emphasis on multiresolution and multi-rate signal processing, especially wavelets and filter banks: theory and applications. He is known for his unique way of teaching for which he received Award for Excellence in Teaching four times from IIT Bombay.
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Teaching Assistant(s)

Yash Sanjay Bhalgat

Mehul Shah

Yash Sanghvi

Shubham Maroti Dhage

 Course Duration : Feb-Apr 2017

  View Course

 Syllabus

 Enrollment : 01-Jan-2017 to 20-Feb-2017

 Exam registration : 30-Jan-2017 to 27-Feb-2017

 Exam Date : 23-Apr-2017

Enrolled

2276

Registered

54

Certificate Eligible

32

Certified Category Count

Gold

1

Elite

15

Successfully completed

16

Participation

9

Success

Elite

Gold





Legend

>=90 - Elite + Gold
60-89 - Elite
40-59 - Successfully Completed
<40 - No Certificate

Final Score Calculation Logic

  • Assignment Score = Average of best 6 out of 8 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
Fundamentals of Wavelets, Filter Banks and Time Frequency Analysis - Toppers list

RUPAM KALYAN CHAKRABORTY 91%

UNIVERSITY COLLEGE OF SCIENCE, TECHNOLOGY & AGRICULTURE

A.BALASUBRAMANIAN 89%

SRI SIVASUBRAMANIYA NADAR COLLEGE OF ENGINEERING

Enrollment Statistics

Total Enrollment: 2276

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