Statistical and Adaptive Signal Processing

Spectral Estimation, Signal Modeling, Adaptive Filtering and Array Processing

Dimitris G. Manolakis, Vinay K. Ingle, Stephen M. Kogon - Collection Signal Processing

796 pages, parution le 19/08/2005

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Résumé

This authoritative volume on statistical and adaptive signal processing offers you a unified, comprehensive and practical treatment of spectral estimation, signal modeling, adaptive filtering, and array processing. Packed with over 3,000 equations and more than 300 illustrations, this unique resource provides you with balanced coverage of implementation issues, applications, and theory, making it a smart choice for professional engineers and students alike.

From the fundamentals of discrete-time signal processing and linear signal models, to optimum linear filters and least-squares filtering and prediction, you get in-depth information on a broad range of critical topics from leading experts in industry and academia. This invaluable reference provides clear examples, problem sets, and computer experiments that help you master the material and learn how to implement various methods presented in the book. You also find a set of Matlab functions that illustrate the use of various techniques and can be used to solve real-world problems in the field.

L'auteur - Dimitris G. Manolakis

Dimitris G. Manolakis is a member of the technical staff at M.I.T. Lincoln Laboratory. Previously, he was a principal member of the research staff at Riverside Research Institute. Dr. Manolakis has taught at the University of Athens, Northeastern University, Boston College, and Worchester Polytechnic Institute. He received his Ph.D. in electrical engineering from the University of Athens, Greece.

L'auteur - Vinay K. Ingle

Vinay K. Ingle is an associate professor of electrical and computer engineering at Northeastern University. He has broad research experience and has taught courses on signal and image processing, stochastic processes, and estimation theory. Dr. Ingle received his Ph.D. in electrical engineering from Rensselaer Polytechnic Institute.

L'auteur - Stephen M. Kogon

Stephen M. Kogon is a member of the technical staff at M.I.T. Lincoln Laboratory. Previously, he has been associated with Raytheon Co., Boston College, and Georgia Tech Research Institute. Dr. Kogon received his Ph.D. in electrical engineering from the Georgia Institute of Technology.

Sommaire

Preface
Introduction
Fundamentals of Discrete-Time Signal Processing
Random Variables, Vectors, and Sequences
Linear Signal Models
Nonparametric Power Spectrum Estimation
Optimum Linear Filters
Algorithms and Structures for Optimum Linear Filters
Least-Squares Filtering and Prediction
Signal Modeling and Parametric Spectral Estimation
Adaptive Filters
Array Processing
Further Topics
Appendix A: Matrix Inversion Lemma
Appendix B: Gradients and Optimization in Complex Space
Appendix C: Matlab Functions
Appendix D: Useful Results from Matrix Algebra
Appendix E: Minimum Phase Test for Polynomials
Bibliography
Index

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Caractéristiques techniques

	PAPIER
Éditeur(s)	Artech House
Auteur(s)	Dimitris G. Manolakis, Vinay K. Ingle, Stephen M. Kogon
Collection	Signal Processing
Parution	19/08/2005
Nb. de pages	796
Format	21 x 26
Couverture	Relié
Poids	1764g
Intérieur	Noir et Blanc
EAN13	9781580536103
ISBN13	978-1-58053-610-3