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 MATLABAr 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 MATLABAr 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 MATLABAr is an ideal companion for quick reference and a perfect, concise introduction to the field.This book - Presents in simple terms the fundamentals of a complicated area of signal processing; Provides a self-contained, easily understood introduction to Wiener filtering, the LMS algorithm, and the least-squares approach; Demonstrates ...
|Title||:||Adaptive Filtering Primer with MATLAB|
|Author||:||Alexander D. Poularikas, Zayed M. Ramadan|
|Publisher||:||CRC Press - 2006-02-14|