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Adaptive Filter Theory, 4th Edition
SubjectDSP, FFT, Waves
ISBN/SKU0130901261
AuthorSimon Haykin
PublisherPrentice Hall PTR
Publish DateSeptember 2001
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Summary

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
Table of 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.

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