January 27, 2005
Gonzalo R. Arce
Nonlinear Signal Processing: A Statistical Approach focuses on unifying the study of a broad and important class of nonlinear signal processing algorithms which emerge from statistical estimation principles, and where the underlying signals are non-Gaussian, rather than Gaussian, processes. Notably, by concentrating on just two non-Gaussian models, a large set of tools is developed that encompass a large portion of the nonlinear signal processing tools proposed in the literature over the past several decades.
Key features include:
Numerous problems at the end of each chapter to aid development and understanding
Examples and case studies provided throughout the book in a wide range of applications bring the text to life and place the theory into context
A set of 60+ MATLAB software m-files allowing the reader to quickly design and apply any of the nonlinear signal processing algorithms descri-bed in the book to an application of interest is available on the accom-panying FTP site.
Publisher: Wiley
Published: November 2004
ISBN: 0-471-67624-1 (Hardcover)