10:00pm-12:00noon Monday; 1:30pm-3:30pm Wednesday (ED609)
Please make an appointment in advance (請儘可能事先預約時段)
The goal of this course is to introduce to seniors and graduate students the principles and applications of adaptive signal processing. Adaptive signal processing has a wide variety of applications, particularly, in digital communication systems, radar, biomedical engineering and others. This course provides a compressive coverage of the basic principles of adaptation. It covers various adaptive signal processing algorithms such as the LMS algorithm and some applications, such as adaptive interference canceling, noise cancellation, etc.
* This course may be lectured in English if it is requested by the students. (如有需求，本課程可能用英語授課。)
- The Final Scores of this course are attached below. Please contact me before June 30, if you have any question about your final scores. Otherwise, the scores are NOT changed after June 30. Grades 本課程學期成績如附檔，如有問題，務必與老師在6月30日前連絡上，逾期不能更動分數。
B. Farhang-Boroujeny, Adaptive Filters: Theory and Applications, Wiley 1998.
(1) B. Widrow and S. Stearns, Adaptive Signal Processing, Prentice Hall, 1985.
(2) A.H. Sayed, Adaptive Filters, Wiley-Interscience, 2008.
(3) S. Haykin, Adaptive Filter Theory, 4th Ed. Prentice-Hall, 2002.
Homework: 15 % (6 HW sets)
Matlab exercises and reports: 25% (3-4 exercises)
Final Examine: 30% (2 hours, two pages of A4 size notes)
Final project (oral and written report): 30%
Signals & Systems, Digital Signal Processing, Stochastic Processes (Principles of Communication Systems, Digital Communications)
(1) Introduction (updated 3.03)
(2) Random Signals (updated 3.03)
(3) Wiener Filters
(4) Search Methods (updated 4.12)
(5) Least-Mean-Square Algorithm
(6) Lattice Adaptive Filters
(7) Least-Squares Algorithm (pp.9-12, updated: 5/15)
(8) Fast RLS Algorithm
(9) Block Implementation of Adaptive Filters
(3) HW3 (Due date: 5.16)
(3S) HW3 Sols
(4) HW4 matlab code: rlsI (Due date: 5.25)
(4S) HW4 Sols