Items related to Adaptive Filter Theory
Synopsis
Adaptive Filter Theory, 4e, is ideal 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 fourth 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.
"synopsis" may belong to another edition of this title.
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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Adaptive Filter Theory, 4e
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Adaptive Filter Theory, 4E
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Adaptive Filter Theory
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Adaptive Filter Theory (4th Edn)
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Adaptive Filter Theory
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Adaptive Filter Theory
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Adaptive Filter Theory
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Adaptive Filter Theory
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Adaptive Filter Theory
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