Contents
- Introduction (Cap1.pdf).
- Stationary processes, models and spectral density (Cap2.pdf).
- Wiener filters. (Cap3.pdf).
- Linear prediction (Cap4.pdf).
- Kalman filters (Cap5.pdf).
- Method of the Steepest Descent (Cap6.pdf).
- Least Mean Squared algorithm (Cap7.pdf).
- Frequency domain adaptive filtering (Cap8.pdf).
- Recursive Least Square algorithms (Cap9.pdf).
- Tracking performance of time varying systems (Cap10.pdf).
- Finite length effects of adaptive filters (Cap11.pdf).
- Detailed contents can be found here (in spanish)
- Course passing requirements: homeworks and final project.
- Bibliography
- P.S.R. Diniz, Adaptive Filtering: Algorithms and Practical Implementation. Springer Ed.
- S. Haykin, Adaptive Filter Theory, Prentice-Hall, Englewood Cliffs, NJ.
- B. Widrow and S. Stearns, Adaptive Signal Processing , Prentice-Hall, Englewood Cliffs, NJ.
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