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 Adaptive Filter Theory
  

  Adaptive Filter Theory by Walter Harrison ; Linda Bamber ; Simon Haykin

  • Published by: PRENTICE-HALL
  • Author: Walter Harrison ; Linda Bamber ; Simon Haykin
  • Page Count: 936
  • Group: GENERAL
  • ISBN: 0130484342/9780130484345
  • Published: n/a

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Book Information and Description:

Adaptive Filter Theory
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

CONTENTS:

Background and Overview.

 1. Stochastic Processes and Models.

 2. Wiener Filters.

 3. Linear Prediction.

 4. Method of Steepest Descent.

 5. Least-Mean-Square Adaptive Filters.

 6. Normalized Least-Mean-Square Adaptive Filters.

 7. Transform-Domain and Sub-Band Adaptive Filters.

 8. Method of Least Squares.

 9. Recursive Least-Square Adaptive Filters.

10. Kalman Filters as the Unifying Bases for RLS Filters.

11. Square-Root Adaptive Filters.

12. Order-Recursive Adaptive Filters.

13. Finite-Precision Effects.

14. Tracking of Time-Varying Systems.

15. Adaptive Filters Using Infinite-Duration Impulse Response Structures.

16. Blind Deconvolution.

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.

Abbreviations.

Principal Symbols.

Bibliography.

Index.