Theory of Wavelet Transform and Its Applications

Theory of Wavelet Transform and Its Applications
Hours: 3 0 3

Introduction of filters; down sampling and up sampling; filter banks; orthogonal filter banks; analysis and synthesis of signals; time-frequency analysis; the short-time Fourier transform; an orthogonal basis of functions; time-scale analysis; the continuous wavelet transform; comparison with STFT; examples of wavelets; analysis and synthesis with wavelets; the Haar wavelet; multiresolution analysis; the scaling function; discrete wavelet transform; filter banks and DWT; numerical complexity of DWT; cascade algorithm; designing wavelets; K-regular scaling filters; characterizing , Characterizing K-regular scaling filters; The Daubechies Maximally Flat Polynomial.

Pre-requisites: noneCo-requisites: none

Hours: XYZ where X = Lecture, Y = Lab, Z = Credit
All hours are per week.
3 Lab hours constitute 1 credit hour
1 credit hour implies 1 lecture of 50mins per academic week. 16 weeks in total.
Pre-Requisite courses are courses required to be completed before this course may be taken
Co-Requisite courses are courses required to be taken along with this course

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