Synopsis
This detail-oriented text is intended for engineers and applied mathematicians who must write computer programs to perform wavelet and related analysis on real data. It contains an overview of mathematical prerequisites and proceeds to describe hands-on programming techniques to implement special programs for signal analysis and other applications. From the table of contents: - Mathematical Preliminaries - Programming Techniques - The Discrete Fourier Transform - Local Trigonometric Transforms - Quadrature Filters - The Discrete Wavelet Transform - Wavelet Packets - The Best Basis Algorithm - Multidimensional Library Trees - Time-Frequency Analysis - Some Applications - Solutions to Some of the Exercises - List of Symbols - Quadrature Filter Coefficients
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About the Author
Mladen Victor Wickerhauser is professor of mathematics and statistics at Washington University, St. Louis. He holds a PhD from Yale University. Professor Wickerhauser’s research interests include harmonic analysis, wavelets, and numerical algorithms for data compression. He has six US patents and 118 publications, one of which led to an algorithm used by the FBI to encode fingerprint images.
From the Back Cover
This detail-oriented text is intended for engineers and applied mathematicians who must write computer programs to perform wavelet and related analyses on real data. It should also be useful to the pure mathematician with questions about wavelet theory applications and to the instructor as a textbook in the mathematics and latest techniques of transient signal analysis and processing. Beginning with an overview of mathematical prerequisites, successive chapters rigorously examine the properties of waveforms used in adapted wavelet analysis: discrete "fast" Fourier transforms, orthogonal and biorthogonal wavelets, wavelet packets, and localized trigonometric or lapped orthogonal functions. Other chapters discuss the "best-basis" method, time-frequency analysis, and combinations of these algorithms useful for signal analysis, denoising, and data compression. Each chapter discusses the technical aspects of implementation, giving examples in pseudocode backed up with a Standard C source code (available on optional diskette), and closes with a list of worked exercises.
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Adapted Wavelet Analysis from Theory to Software.
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Wellesley MA, A K Peters., 1994
ISBN 10: 1568810415
ISBN 13: 9781568810416
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Adapted Wavelet Analysis from Theory to Software
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A K Peters Ltd, Natick, Massachusetts, U.S.A., 1994
ISBN 10: 1568810415
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