Adaptive System Identification and Signal Processing Algorithms

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Editorial Reviews

Booknews
A state-of-the-art account of the most important performance features of a widely used class of algorithmic families for adaptive system identification and signal processing. Important issues such as convergence, tracking, numerical accuracy and stability, computational complexity and parallelism are addressed and discussed in depth. Each chapter discusses the basic related concepts and mathematical proofs in such detail so as to remain rigorous, on the one hand and, on the other, to make the text readable not only to theoreticians but to users as well. Annotation c. Book News, Inc., Portland, OR (booknews.com)
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Product Details

Table of Contents

List of contributors
Preface
1 Introduction 1
2 Basic Concepts and Algorithmic Schemes 7
3 General Structure of Adaptive Algorithms: Adaptation and Tracking 58
4 The Least Mean Square Family 84
5 Fast Transversal RLS Algorithms 123
6 Lattice algorithms 191
7 The QR family 260
8 Spectral analysis 322
9 Channel equalization 388
10 Echo cancellation 407
11 Interference rejection and channel estimation for spread-spectrum communications 466
12 Neural networks for adaptive signal processing 512
Index 554
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