Adaptive Filter Theory (Prentice-Hall Information and System Sciences Series)

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9780130132369: Adaptive Filter Theory (Prentice-Hall Information and System Sciences Series)
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This book develops the mathematical theory of linear adaptive filters with finite impulse response. Examples and computer experiment applications illustrate the theory and principles. The second edition has also been restructured with an introduction followed by four parts: discrete-time wide-sense station stochastic process; linear optimum filtering; linear FIR adaptive filtering; limitations, extensions and discussions. New features includes new chapters on QR decomposition-based lattice filters, on blind deconvolution, new appendix material on complex variables and regulation.

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From the Publisher:

Haykin examines both the mathematical theory behind various linear adaptive filters with finite-duration impulse response (FIR) and the elements of supervised neural networks. The Third Edition of this highly successful book has been updated and refined to keep current with the field and develop concepts in as unified and accessible a manner as possible.

From the Back Cover:

CONTENTS

Preface
Acknowledgments
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 Least-Mean-Square Adaptive Filters
  • Chapter 6 Normalized Least-Mean-Square Adaptive Filters
  • Chapter 7 Frequency-Domain and Subband Adaptive Filters
  • Chapter 8 Method of Least Squares
  • Chapter 9 Recursive Least-Square Adaptive Filters
  • Chapter 10 Kalman Filters
  • Chapter 11 Square-Root Adaptive Filters
  • Chapter 12 Order-Recursive Adaptive Filters
  • Chapter 13 Finite-Precision Effects
  • Chapter 14 Tracking of Time-Varying Systems
  • Chapter 15 Adaptive Filters Using Infinite-Duration Impulse Response Structures
  • Chapter 16 Blind Deconvolution
  • Chapter 17 Back-Propagation Learning

Epilogue

  • Appendix A Complex Variables
  • Appendix B Differentiation with Respect to a Vector
  • Appendix C Method of Lagrange Multipliers
  • Appendix D Estimation Theory
  • Appendix E Eigenanalysis
  • Appendix F Rotations and Reflections
  • Appendix G Complex Wishart Distribution
  • Glossary
  • Bibliography
  • Index

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