Random Processes

Filtering, Estimation and Detection

Lonnie C. Ludeman

626 pages, parution le 31/01/2003

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Résumé

An understanding of random processes is crucial to many engineering fields-including communication theory, computer vision, and digital signal processing in electrical and computer engineering, and vibrational theory and stress analysis in mechanical engineering. The filtering, estimation, and detection of random processes in noisy environments are critical tasks necessary in the analysis and design of new communications systems and useful signal processing algorithms. Random Processes: Filtering, Estimation, and Detection clearly explains the basics of probability and random processes and details modern detection and estimation theory to accomplish these tasks.

In this book, Lonnie Ludeman, an award-winning authority in digital signal processing, joins the fundamentals of random processes with the standard techniques of linear and nonlinear systems analysis and hypothesis testing to give signal estimation techniques, specify optimum estimation procedures, provide optimum decision rules for classification purposes, and describe performance evaluation definitions and procedures for the resulting methods. The text covers four main, interrelated topics:

Probability and characterizations of random variables and random processes
Linear and nonlinear systems with random excitations
Optimum estimation theory including both the Wiener and Kalman Filters
Detection theory for both discrete and continuous time measurements

Lucid, thorough, and well-stocked with numerous examples and practice problems that emphasize the concepts discussed, Random Processes: Filtering, Estimation, and Detection is an understandable and useful text ideal as both a self-study guide for professionals in the field and as a core text for graduate students.

Contents

Experiments and Probability
Random Variables
Estimation of Random Variables
Random Processes
Linear Systems: Random Processes
Nonlinear Systems: Random Processes
Optimum Linear Filters: The Wiener Approach
Optimum Linear Systems: The Kalman Approach
Detection Theory: Discrete Observation
Detection Theory: Continuous Observation

Appendix A. The Bilateral Laplace Transform
Appendix B. Table of Binomial Probabilities
Appendix C. Table of Discrete Random Variables and Properties
Appendix D. Table of Continuous Random Variables and Properties
Appendix E. Table of Gaussian Cumulative Distribution Function

L'auteur - Lonnie C. Ludeman

LONNIE C. LUDEMAN, PhD, received his doctorate from Arizona State University and is Professor Emeritus of electrical and computer engineering at New Mexico State University. In 1993, he was a Fulbright Scholar at the Aristotle University in Thessaloniki, Greece. He is the author of Fundamentals of Digital Signal Processing, which won Choice magazine's award for Outstanding Engineering Book of the Year.

Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Lonnie C. Ludeman
Parution	31/01/2003
Nb. de pages	626
Format	16 x 24
Couverture	Relié
Poids	1000g
Intérieur	Noir et Blanc
EAN13	9780471259756
ISBN13	978-0-471-25975-6