FUNDAMENTALS OF WAVELETS：THEORY, ALGORITHMS, AND APPLICATIONS

Wavelet theory originated from research activities in many areas of science and engineering. As a result, it finds applications in a wide range of practical problems. Wavelet techniques are specifically suited for nonstationary signals for which classic Fourier methods are ineffective.

Based on courses taught by the authors at Texas A&M University as well as related conferences, Fundamentals of Wavelets is a textbook offering an up-to-date engineering approach to wavelet theory. It balances a discussion of wavelet theory and algorithms with its far-ranging practical applications in signal processing, image processing, electromagnetic wave scattering, and boundary value problems.

In a clear, progressive format, the book describes:
* Basic concepts of linear algebra, Fourier analysis, and discrete signal analysis
* Theoretical aspects of time-frequency analysis and multiresolution analysis
* Construction of various wavelets
* Algorithms for computing wavelet transformations.

Concluding chapters present interesting applications of wavelets to signal processing and boundary value problems. Fundamentals of Wavelets is an essential introduction to wavelet theory for students and professionals alike in a practical, real-world engineering context.

JAIDEVA C. GOSWAMI is an engineer at Schlumberger Well Services in Sugar- land, Texas. He has taught several short courses on wavelets and contributed to the Encyclopedia of Electrical and Electronics Engineering. Dr. Goswami received his PhD in electrical engineering from Texas A&M University.

ANDREW K. CHAN is on the faculty of Texas A&M University and the coauthor of Wavelets in a Box and Wavelet Toolware. Dr. Chan received his PhD in electrical engineering from the University of Washington.

What This Book Is About?

Mathematical Preliminaries.

Fourier Analysis.

Time-Frequency Analysis.

Multiresolution Analysis.

Construction of Wavelets.

Discrete Wavelet Transform and Filter Bank Algorithms.

Fast Integral Transform and Applications.

Digital Signal Processing Applications.

Wavelets in Boundary Value Problems.

Index.