Read more
This book addresses the properties of wavelet and related transforms, to establish criteria by which the proper analysis tool may be chosen, and details software implementations to perform the needed computation. It is useful for the pure mathematician who is familiar with parts of wavelet theory.
List of contents
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
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.
Summary
This book addresses the properties of wavelet and related transforms, to establish criteria by which the proper analysis tool may be chosen, and details software implementations to perform the needed computation. It is useful for the pure mathematician who is familiar with parts of wavelet theory.
