Fundamentals of Adaptive Filtering

Ali H. Sayed

1126 pages, parution le 04/07/2003

Ajouter à une liste

Indisponible

Résumé

This book is based on a graduate level course offered by the author at UCLA and has been classed tested there and at other universities over a number of years. This will be the most comprehensive book on the market today providing instructors a wide choice in designing their courses.

Offers computer problems to illustrate real life applications for students and professionals alike
There will be an Instructor's Manual presenting detailed solutions to all the problems in the book

Notation
Symbols
Optimal Estimation
Linear Estimation
Constrained Linear Estimation
Steepest-Descent Algorithms
Stochastic-Gradient Algorithms
Steady-State Performance of Adaptive Filters
Tracking Performance of Adaptive Filters
Finite Precision Effects
Transient Performance of Adaptive Filters
Block Adaptive Filters
The Least-Squares Criterion
Recursive Least-Squares
RLS Array Algorithms
Fast Fixed-Order Filters
Lattice Filters
Laguerre Adaptive Filters
Robust Adaptive Filters
Bibliography
Author Index
Subject Index

Caractéristiques techniques

	PAPIER
Éditeur(s)	Wiley
Auteur(s)	Ali H. Sayed
Parution	04/07/2003
Nb. de pages	1126
Format	21 x 26
Couverture	Relié
Poids	2450g
Intérieur	Noir et Blanc
EAN13	9780471461265
ISBN13	978-0-471-46126-5