Nonlinear Signal Processing : A Statistical Approach

Nonlinear Signal Processing : A Statistical Approach

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Book Description
A Unified Treatment of Non-Gaussian Processes and Nonlinear Signal Processing

Nonlinear signal processing methods are finding numerous applications in such fields as imaging, teletraffic, communications, hydrology, geology, and economics-fields where nonlinear systems and non-Gaussian processes emerge. Within a broad class of nonlinear signal processing methods, this book provides a unified treatment of optimal and adaptive signal processing tools that mirror those of Wiener and Widrow, extensively presented in the linear filter theory literature. The methods detailed in this book can thus be tailored to effectively exploit non-Gaussian signal statistics in a system or its inherent nonlinearities to overcome many of the limitations of the traditional practices used in signal processing.

Chapters include:

A review of non-Gaussian models, with an emphasis on the class of generalized Gaussian distributions and the class of stable distributions
The basic principles of order statistics
Maximum likelihood and robust estimation principles
Signal processing tools based on weighted medians and stack filters
Filters based on linear combinations of order statistics and various generalizations
Signal processing methods tailored for signals described by stable distributions

Numerous problems, examples, and case studies enable rapid mastery of the topics discussed, and over 60 MATLAB m-files allow the reader to quickly design and apply the algorithms to any application.

Download Description
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 described in the book to an application of interest is available on the accompanying FTP site.

--This text refers to the Digital edition.

Nonlinear Signal Processing : A Statistical Approach

Nonlinear Signal Processing: A Statistical Approach,Gonzalo R. Arce,Wiley-Interscience,0471676241,Engineering - Electrical & Electronic,Mathematical Statistics,Mathematics,Microwaves,Probability & Statistics - General,Science,Science/Mathematics,Signal Processing (Communication Engineering),Signal processing,Statistics,Technology,Technology & Industrial Arts,Telecommunications,Waves & Wave Mechanics,Communications engineering / telecommunications,Science / Waves & Wave Mechanics

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