Adaptive Filter Theory: Pearson International Edition VitalSource eText (5e) : 9780273775720

Adaptive Filter Theory: Pearson International Edition VitalSource eText (5e)

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Pearson Higher Ed USA
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About the book

For courses in Adaptive Filters.

Haykin examines both the mathematical theory behind various linear adaptive filters and the elements of supervised multilayer perceptrons. In its fifth edition, this highly successful book has been updated and refined to stay current with the field and develop concepts in as unified and accessible a manner as possible.

Table of contents
Background and Preview

Chapter 1 Stochastic Processes and Models

Chapter 2 Wiener Filters

Chapter 3 Linear Prediction

Chapter 4 Method of Steepest Descent

Chapter 5 Method of Stochastic Gradient Descent

Chapter 6 The Least-Mean-Square (LMS) Algorithm

Chapter 7 Normalized Least-Mean-Square (LMS) Algorithm and Its Generalization

Chapter 8 Block-Adaptive Filters

Chapter 9 Method of Least Squares

Chapter 10 The Recursive Least-Squares (RLS) Algorithm

Chapter 11 Robustness

Chapter 12 Finite-Precision Effects

Chapter 13 Adaptation in Nonstationary Environments

Chapter 14 Kalman Filters

Chapter 15 Square-Root Adaptive Filters

Chapter 16 Order-Recursive Adaptive Filters

Chapter 17 Blind Deconvolution


Appendix A Theory of Complex Variables

Appendix B Computation of Derivatives in the Complex Domain

Appendix C Method of Lagrange Multipliers

Appendix D Estimation Theory

Appendix E Eigenanalysis

Appendix F Langevin Equation of Nonequilibrium Thermodynamics

Appendix G Rotations and Reflections

Appendix H Complex Wishart Distribution

Suggested Readings
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