Course Details
Subject {L-T-P / C} : EE6143 : Signal Transforms { 3-0-0 / 3}
Subject Nature : Theory
Coordinator : Dr. Supratim Gupta
Syllabus
Introduction to signal transforms: Orthonormal vector and functional space and variations Metric Preservation: Parseval’s Theorem in orthonormal space Hilbert Transform, Hilbert-Huang Transform Fourier transform, Fourier series, Generalized Fourier transform property and convolution theorem Discrete Cosine Transform (DCT), Discrete Sine Transform (DST), Short Time Fourier Transform (STFT) Wavelet Transform: Method & Properties, Multi-resolution analysis, M Band QMF filter banks Quantization and coding of transform coefficients Frame Theory: Signal approximation & compressed sampling, Parseval’s Theorem in redundant space, Curvelet transform & beyond: Method & Properties.
Course Objectives
- To make the students adept to visualizing the domain of signal transforms
- To make the students adept to represent signals in compact transform domain
- To make the students adept to develop algorithms to map from signal to other transform domain
- To make the students adept to implement the algorithm in software/Hardware
Course Outcomes
• The student will be aware and able to visualize the domain of signal transforms <br />• The student will be able to represent signals in the compact transform domain <br />• The student will be able to develop algorithms to map from signal to other transform domain <br />• The student will be able to implement the algorithm in software/Hardware
Essential Reading
- Truong Nguyen & Gilbert Strang, Wavelets and Filter Banks, Wellesley-Cambridge Press , Latest Ed.
- K. R. Rao and P. Yip, Discrete Cosine Transform: Algorithms, Advantages, Applications, Academic Press , Latest Ed.
Supplementary Reading
- Khalid Sayood, Introduction to Data Compression, Elsevier , 2011 or Latest Ed.
- Gilbert Strang, Linear Algebra and Its Applications, Nelson Engineering , 2007 or Latest Ed.