Adaptive Filter Theory:United States Edition

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CONTENTSPrefaceAcknowledgmentsBackground 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 EpilogueAppendix 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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