Statistical Digital Signal Processing and Modeling / Edition 1

by Monson H. Hayes

Overview

This new text responds to the dramatic growth in digital signal processing (DSP) over the past decade, and is the product of many years of teaching an advanced DSP course at Georgia Tech. While the focal point of the text is signal modeling, it integrates and explores the relationships of signal modeling to the important problems of optimal filtering, spectrum estimation, and adaptive filtering.

Coverage is equally divided between the theory and philosophy of statistical signal processing, and the algorithms that are used to solve related problems. The text reflects the author's philosophy that a deep understanding of signal processing is accomplished best through working problems. For this reason, the book is loaded with worked examples, homework problems, and MATLAB computer exercises. While the examples serve to illustrate the ideas developed in the book, the problems seek to motivate and challenge the student and the computer exercises allow the student to experiment with signal processing algorithms on complex signals.

Professor Hayes is recognized as a leader in the signal processing community, particularly for his work in signal reconstruction and image processing. This text is suitable for senior/graduate level courses in advanced DSP or digital filtering found in Electrical Engineering Departments. Prerequisites include basic courses in DSP and probability theory.

Product Details

ISBN-13:	9780471594314
Publisher:	Wiley
Publication date:	04/19/1996
Pages:	624
Product dimensions:	7.28(w) x 10.26(h) x 1.08(d)

About the Author

Monson H. Hayes is the author of Statistical Digital Signal Processing and Modeling, published by Wiley.

Table of Contents

Background.

Discrete-Time Random Processes.

Signal Modeling.

The Levinson Recursion.

Lattice Filters.

Wiener Filtering.

Spectrum Estimation.

Adaptive Filtering.

Appendix.

Table of Symbols.

Index.

Editorial Reviews

A textbook for a one-quarter or one-semester senior or graduate second course in discrete-time signal processing. Assumes a knowledge of difference equations, discrete convolution and linear filtering, the discrete-time Fourier transform, the zeta- transform, and linear algebra. Many of the problems are presented in Matlab. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Booknews