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UCLA Adaptive Systems Laboratory

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Video Lectures (20)

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Important Copyright Information. Copyright Ali H. Sayed, 2008. All rights reserved. These lectures can be watched on this site but cannot be copied. The lectures can be watched by instructors and students for instructional and educational purposes only. The lectures cannot be downloaded and/or distributed. Image

Note for Instructors: A complete solutions manual is available upon request from the publisher or the author. Solutions to all computer projects in the book, including MATLAB code, can be downloaded here:
  1. Download MATLAB programs for solving all computer projects.
  2. Download plots and solutions for all computer projects.
  3. Download additional assignment problems.

  4. Download errata. [pdf]

Content: These lectures provide a thorough and unified treatment of adaptive filters and their performance. The lectures cover the fundamentals of linear estimation theory, adaptive filtering, mean-square performance, and least-squares theory. Necessary background from linear algebra and probability theory is also covered.

Textbook Information: A. H. Sayed, Adaptive Filters, John Wiley & Sons, NJ, ISBN 978-0-470-25388-5, xxx+786pp, 2008.

Disclaimer: The lectures have been recorded using a simple studio set-up. An effort has been made to limit the lectures to at most 120mins each. Please excuse imperfections.

  1. Video Lecture 1 (97 mins): Mean-Square Error Estimation (Scalar Case), Sections A.1, A.2, 1.1-1.3

  2. Video Lecture 2 (106 mins): Mean-Square Error Estimation (Vector Case), Sections A.3, A.4, B.1, 2.1-2.3

  3. Video Lecture 3 (106 mins): Linear Estimation, Appendix C and Sections 3.1-3.4, 4.2

  4. Video Lecture 4 (100 mins): Normal Equations and Design Examples, Sections B.2, 4.1, 4.3, 4.4

  5. Video Lecture 5 (86 mins): Linear Models and Applications, Sections 5.1-5.5

  6. Video Lecture 6 (109 mins): Constrained Estimation and Applications, Sections 6.1-6.3

  7. Video Lecture 7 (99 mins): Kalman Filtering, Sections 7.1-7.7

  8. Video Lecture 8 (113 mins): Steepest-Descent Algorithms, Sections 8.1-8.3, 9.1-9.8

  9. Video Lecture 9 (115 mins): Stochastic-Gradient Algorithms, Sections 10.1-10.3, 10.5-10.8, 11.1-11.3, Chapter 12, Sections 13.1, 14.1

  10. Video Lecture 10 (116 mins): Mean-Square Performance and Energy Conservation, Sections 15.1-15.4, 16.1-16.6, 19.3

  11. Video Lecture 11 (93 mins): Tracking Performance and Energy Conservation, Sections 20.1-20.4, 21.1, 21.6

  12. Video Lecture 12 (114 mins): Transient Performance and Energy Conservation, Sections 22.1-22.4, 23.1-23.5, 24.1

  13. Video Lecture 13 (98 mins): Transient Performance of LMS, Sections23.2-23.5, 24.1

  14. Video Lecture 14 (104 mins): Least-Squares Methods, Sections 29.1-29.3, 29.5-29.8, 30.1-30.6

  15. Video Lecture 15 (120 mins): Recursive Least-Squares: Sections B.6, 30.1-30.6, 33.1-33.4

  16. Video Lecture 16 (97 mins): Unitary Transformations: Sections 33.4, 34.1-34.2, 36.1-36.3

  17. Video Lecture 17 (117 mins): Array RLS Algorithms, Sections 35.1-35.2, 37.1-37.4

  18. Video Lecture 18 (100 mins): Order and Time-Update Relations, Sections 32.1-32.3

  19. Video Lecture 19 (102 mins): Order-Recursive Least-Squares, Sections 40.1-40.5

  20. Video Lecture 20 (84 mins): Lattice Filters, Sections 41.1-41.3

Assignments: Examples of homework assignments that can go along with these lectures:
  1. Homework 1: Solve problems I.13, I.14, I.16, I.18, I.19, I.21. Run computer project I.1 and attach solution plots.

  2. Homework 2: Solve Problems II.7, II.14, II.17, II.18, II.19, and II.23. Run Computer Project II.1 and attach the simulation plots.

  3. Homework 3: Solve Problems II.20, II.21, II.22, II.25, II.31, II.36, and II.37. Run Computer Project II.3 and attach simulation results.

  4. Homework 4: Solve Problems II.48, II.49, III.12, III.15, III.18, and III.22. Run Computer Project III.1 and attach solution plots.

  5. Homework 5: Solve Problems III.26, III.29, III.33, III.45, IV.2, IV.3, IV.4, and IV.14. Run Computer Project III.3 and attach solution plots.

  6. Homework 6: Solve Problems IV. 26, IV.28, IV.38, IV.39, V.4, V.5, V.9, and V.11. Run Computer Project IV.1 and attach solution plots.

  7. Homework 7: Solve Problems V.14, V.21, V.24, V.38, VII.3, VII.12,VII.19, and VII.20. Run Computer Project V.1 and attach solution plots.

  8. Homework 8: Solve Problems VII.30, VII.33, VII.35, VII.40, VIII.3, VIII.4, and VIII.11. Run Computer Project VII.1 and attach solution plots.

  9. Homework 9: Solve Problems X.1, X.3, X.7, X.9, and X.10. Run Computer Project X.1 and attach simulation plots.