Digital Signal Processing Using Matlab and Wavelets: .

by Michael Weeks

Although DSP has long been considered an EE topic, recent developments have also generated significant interest from the computer science community. DSP applications in the consumer market, such as bioinformatics, the MP3 audio format, and MPEG-based cable/satellite television have fueled a desire to understand this technology outside of hardware circles. Designed for upper division engineering and computer science students as well as practicing engineers, Digital Signal Processing Using Matlab and Wavelets emphasizes the practical applications of signal processing. Over 100 Matlab projects and wavelet techniques provide the latest applications of DSP, including image processing, games, filters, transforms, networking, parallel processing, and sound. The book also provides the mathematical processes and techniques needed to ensure an understanding of DSP theory. Designed to be incremental in difficulty, the book will benefit readers who are unfamiliar with complex mathematical topics or those limited in programming experience. Beginning with an introduction to Matlab programming, it moves through filters, sinusoids, sampling, the Fourier transform, the Z transform and other key topics. An entire chapter is dedicated to the discussion of wavelets and their applications. A CD-ROM (platform independent) accompanies the book and contains source code, projects, and Microsoft® PowerPoint slides.

Genres: Mathematics

452 pages, Hardcover

First published September 15, 2006

About the author

Michael Weeks is an amateur historian with a passion for the road. He has driven tens of thousands of miles across America in search of the living roots of U.S. history. Weeks lives in the South Loop area of Chicago, Illinois, with his wife, Charlotte, and works as an occupational health and safety consultant. Although Weeks is the author of a comprehensive road-trip guide, ironically, he does not own a car."

Reviews

[Darin]

This is an undergraduate-level book in signal processing, but the title of this book is misleading since only one out of ten chapters is devoted to wavelets. Wavelets are described from the digital signal processing perspective, so I guess the preceding eight chapters (chapter 9 is wavelets; chapter 10 is applications) are intended to get people to the point to where they can understand the wavelet discussion. If you want a simple, undergraduate-level introduction to signal processing, then this book seems OK, but if you want a book on wavelets then you may wish to look elsewhere.