Dr. Andre Manitius
Tel.: 993-1569, e-mail:
amanitiu@gmu.edu
Required Textbook
Widrow and Stearns, Adaptive Signal
Processing, Prentice Hall 1985
Recommended
1. The Student Edition of MATLAB,
recent edition
2. Haykin, Adaptive Filter Theory,
3rd Ed, Prentice Hall, 1996
Computational experiments will be required, using Matlab.
Final grades will be determined by a weighted average of the homework, the two tests and the final exam.
Tentative Course Schedule - Spring 2007
Exact dates are not yet posted because there could be some changes
| Week 1 |
General Introduction to Adaptive Systems and Signal Processing |
| Week 2 |
Correlation Functions, their Unbiased Estimates. Correlation Matrix. |
| Week 3 |
Properties of Correlation Matrices. Power spectral density. |
| Week 4 |
Quiz 1 + Search of Minimum. Steepest Descent and Newton Algorithms |
| Week 5 |
The LMS algorithm, and the RLS Algorithm. |
| Week 6 |
More on the LMS Algorithm. Examples. |
| Week 7 |
Test 1 + Performance of the LMS Algorithm. LMS/Newton. |
| Week 8 |
Spring Break |
| Week 9 |
SER and RLS Algorithm, with and without forgetting factor. |
| Week 10 |
Other adaptive algorithms + Adaptive Modeling. |
| Week 11 |
Quiz 2 + Adaptive Channel Equalization. |
| Week 12 |
Adaptive Equalization, Adaptive Interference Cancellation |
| Week 13 |
Test 2 + more on Adaptive Interference Cancellation |
| Week 14 |
Adaptive Arrays, Project Review |
| Week 15 |
More on Adaptive Arrays,
and Project Review (last class) |
Final
Exam date by GMU Calendar