Adapted Wavelet Analysis

From Theory to Software
1. Auflage 2019
ISBN: 978-0-367-44860-8
Verlag: A K Peters/CRC Press

Buch, Englisch, 498 Seiten, Format (B × H): 152 mm x 229 mm, Gewicht: 717 g

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

Zielgruppe

Academic and Professional Practice & Development

Autoren/Hrsg.

Wickerhauser, Mladen Victor

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle

Inhaltsverzeichnis

1. Mathematical Preliminaries 2. Programming Techniques 3. The Discrete Fourier Transform 4. Local Trigonometric Transforms 5. Quadrature Filters 6. The Discrete Wavelet Transform 7. Wavelet Packets 8. The Best Basis Algorithm 9. Multidimensional Library Trees 10. Time-Frequency Analysis 11. Some Applications

Über Autor(innen)

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.