Adaptive filter theory
Author(s)
Bibliographic Information
Adaptive filter theory
（Prentice-Hall information and system sciences series）
Prentice-Hall, c2002
4th ed
Available at / 42 libraries
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Prefectural University of Hiroshima Library and Academic Information Center
549.3||H49110011229
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Note
Includes bibliographical references (p. 870-911) and index
Description and Table of Contents
Description
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.
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.
by "Nielsen BookData"
