
Adaptive Filtering Primer with MATLAB
CRC Press
1st Edition
Published on 14. February 2006
Book
Paperback/Softback
238 pages
978-0-8493-7043-4 (ISBN)
Description
Because of the wide use of adaptive filtering in digital signal processing and, because most of the modern electronic devices include some type of an adaptive filter, a text that brings forth the fundamentals of this field was necessary. The material and the principles presented in this book are easily accessible to engineers, scientists, and students who would like to learn the fundamentals of this field and have a background at the bachelor level.
Adaptive Filtering Primer with MATLAB (R) clearly explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. The authors introduce discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm. They also supply many MATLAB (R) functions and m-files along with computer experiments to illustrate how to apply the concepts to real-world problems. The book includes problems along with hints, suggestions, and solutions for solving them. An appendix on matrix computations completes the self-contained coverage.
With applications across a wide range of areas, including radar, communications, control, medical instrumentation, and seismology, Adaptive Filtering Primer with MATLAB (R) is an ideal companion for quick reference and a perfect, concise introduction to the field.
Adaptive Filtering Primer with MATLAB (R) clearly explains the fundamentals of adaptive filtering supported by numerous examples and computer simulations. The authors introduce discrete-time signal processing, random variables and stochastic processes, the Wiener filter, properties of the error surface, the steepest descent method, and the least mean square (LMS) algorithm. They also supply many MATLAB (R) functions and m-files along with computer experiments to illustrate how to apply the concepts to real-world problems. The book includes problems along with hints, suggestions, and solutions for solving them. An appendix on matrix computations completes the self-contained coverage.
With applications across a wide range of areas, including radar, communications, control, medical instrumentation, and seismology, Adaptive Filtering Primer with MATLAB (R) is an ideal companion for quick reference and a perfect, concise introduction to the field.
More details
Series
Language
English
Place of publication
Bosa Roca
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Undergraduate
Product notice
Paperback (trade)
Unsewn / adhesive bound
Illustrations
78 s/w Abbildungen, 11 s/w Tabellen
11 Tables, black and white; 78 Illustrations, black and white
Dimensions
Height: 229 mm
Width: 199 mm
Thickness: 13 mm
Weight
340 gr
ISBN-13
978-0-8493-7043-4 (9780849370434)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Alexander D. Poularikas | Zayed M. Ramadan
Adaptive Filtering Primer with MATLAB
E-Book
12/2017
CRC Press
€68.49
Available for download

Alexander D. Poularikas | Zayed M. Ramadan
Adaptive Filtering Primer with MATLAB
E-Book
12/2017
CRC Press
€68.49
Available for download

Alexander D. Poularikas | Zayed M. Ramadan
Adaptive Filtering Primer with MATLAB
Book
07/2017
1st Edition
CRC Press
€290.17
Shipment within 10-20 days
Persons
Alexander D. Poularikas, Zayed M. Ramadan
Author
The University of Alabama, Huntsville, USA
Al Ain University of Science and Technology,United Arab Emir
Content
Introduction. Discrete-Time Signal Processing. Random Variables, Sequences, and Stochastic Processes. Wiener Filters. Eigenvalues of Rx - Properties of the Error Surface. Newton and Steepest-Descent Method. The Least Mean-Square (LMS) Algorithm. Variations of LMS Algorithms. Least Squares and Recursive Least-Squares Signal Processing. Abbreviations. Bibliography. Appendix A: Matrix Analysis. Index.