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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