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NOC:Foundations of Wavelets and Multirate Digital Signal Processing
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NOC:Foundations of Wavelets and Multirate Digital Signal Processing
by Prof. V.M. Gadre

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,...

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About This Course

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,...

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Course Curriculum
5 Sections | 31 Lecture | 09h 04min total length
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NOC:Foundations of Wavelets and Multirate Digital Signal Processing

Module : 1

| 01h 55min total length
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    Introduction

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    Origin of wavelets

    23m <?php echo $alt; ?>
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    Haar wavelet

    16m <?php echo $alt; ?>
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    Dyadic wavelet

    26m <?php echo $alt; ?>
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    Dilates and translates of Haar wavelet

    20m <?php echo $alt; ?>
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    L2 norm of a function

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NOC:Foundations of Wavelets and Multirate Digital Signal Processing

Module : 2

| 01h 36min total length
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    Piecewise constant representation of a function

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    Ladder of subspaces

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    Scaling function of Haar wavelet

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    Demonstration: Piecewise constant approximation of functions

    4m <?php echo $alt; ?>
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    Vector representation of sequences

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    Properties of norm

    15m <?php echo $alt; ?>
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    Parsevals theorem

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NOC:Foundations of Wavelets and Multirate Digital Signal Processing

Module : 3

| 02h 11min total length
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    Equivalence of functions & sequences

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    Angle between Functions & their Decomposition

    25m <?php echo $alt; ?>
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    Additional Information on Direct-Sum

    14m <?php echo $alt; ?>
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    Introduction to filter banks

    17m <?php echo $alt; ?>
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    Haar Analysis filter bank in Z-domain

    9m <?php echo $alt; ?>
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    Haar Synthesis filter bank in Z-domain

    36m <?php echo $alt; ?>
NOC:Foundations of Wavelets and Multirate Digital Signal Processing

Module : 4

| 02h 08min total length
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    Moving from Z-domain to frequency domain

    14m <?php echo $alt; ?>
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    Frequency Response of Haar Analysis Low pass Filter bank

    19m <?php echo $alt; ?>
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    Frequency Response of Haar Analysis High pass Filter bank

    20m <?php echo $alt; ?>
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    Ideal Two-band Filter bank

    18m <?php echo $alt; ?>
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    Disqualification of Ideal Filter bank

    18m <?php echo $alt; ?>
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    Realizable Two-band Filter bank

    20m <?php echo $alt; ?>
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    Demonstration: DWT of images

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NOC:Foundations of Wavelets and Multirate Digital Signal Processing

Module : 5

| 01h 12min total length
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    Relating Fourier transform of scaling function to filter bank

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    Fourier transform of scaling function

    8m <?php echo $alt; ?>
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    Construction of scaling and wavelet functions from filter bank

    24m <?php echo $alt; ?>
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    Demonstration: Constructing scaling and wavelet functions.

    7m <?php echo $alt; ?>
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    Conclusive Remarks and Future Prospects

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show 2 more sections
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