Discrete Random Signal Processing and Filtering Primer with MATLAB
Autor Alexander D. Poularikasen Limba Engleză Paperback – 23 oct 2019
Numerous Useful Examples, Problems, and Solutions – An Extensive and Powerful Review
Written for practicing engineers seeking to strengthen their practical grasp of random signal processing, Discrete Random Signal Processing and Filtering Primer with MATLAB provides the opportunity to doubly enhance their skills. The author, a leading expert in the field of electrical and computer engineering, offers a solid review of recent developments in discrete signal processing. The book also details the latest progress in the revolutionary MATLAB language.
A Practical Self-Tutorial That Transcends Theory
The author introduces an incremental discussion of signal processing and filtering, and presents several new methods that can be used for a more dynamic analysis of random digital signals with both linear and non-linear filtering. Ideal as a self-tutorial, this book includes numerous examples and functions, which can be used to select parameters, perform simulations, and analyze results. This concise guide encourages readers to use MATLAB functions – and those new ones introduced as Book MATLAB Functions – to substitute many different combinations of parameters, giving them a firm grasp of how much each parameter affects results.
Much more than a simple review of theory, this book emphasizes problem solving and result analysis, enabling readers to take a hands-on approach to advance their own understanding of MATLAB and the way it is used within signal processing and filtering.
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Specificații
ISBN-13: 9780367386313
ISBN-10: 0367386313
Pagini: 300
Dimensiuni: 156 x 234 x 19 mm
Greutate: 0.41 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
ISBN-10: 0367386313
Pagini: 300
Dimensiuni: 156 x 234 x 19 mm
Greutate: 0.41 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Public țintă
Academic and Professional Practice & DevelopmentCuprins
Fourier analysis of signals. Random variables, sequences, and stochastic processes. Nonparametric (classical) spectrums estimation. Parametric and other methods for spectra estimation. Optimal filtering—Wiener filters. Adaptive filtering—LMS algorithm. Adaptive filtering with variations of LMS algorithm. Nonlinear filtering. Appendices.
Descriere
Random signal processing is important to many diverse fields, such as communications, seismology, and bioengineering. This book provides a practical introduction to discrete random signal processing and the filtering of signals with both linear and nonlinear filters. Since the signals involved are random, the text also introduces random variables. It presents several new approaches to achieve the desired results and offers all of the background material necessary to understand the concepts described. The authors use a wide range of MATLAB® functions and figures, problems with solutions, and computer examples to illustrate the underlying theory and applications.