- Instructor
- Dr. Andre Manitius
S &T II Room 230C
Tel.: (703) 993-1569
e-mail: amanitiu@gmu.edu
Announcements:
Expected background: I expect students to know enough
about signals and systems, and Matlab, to be able to follow the
lectures and do homeworks quite easily and get good results at the end.
Many students in
the past three semesters have in fact done that.
ECE 535 is not a required prerequisite, but if you have already
completed it with a good grade, this course will be easier for you.
You can also take ECE 535 and ECE 635 concurrently.
- Prerequisite for this course in ECE 528 (or permission of
the instructor). If you have not yet completed ECE 528 but have other
equivalent knowledge or work experience with properties of random
signals, you may attend the course, but I would suggest you discuss
this with me first to determine if you have a good chance to complete
the course without too much extra
work.
- Those who are considering this course, please look at the
textbook to see if the material appears accessible to you.
- We will be using matrices, z-transforms, correlation
functions and power spectral densities, along with some properties of
simple optimization algorithms, and quite a lot of Matlab assignments.
- You will do a project (or an extended homework assignment) on
one of the new methods of adaptive signal processing published in
recent
literature.
- If by any chance you have your own project that is related
to your work, and if the project fits in this course, you may do some
work on such a project for class credit.
- An interesting project in this class may get you started
towards an ECE Scholarly Paper required for graduation with an MS EE
degree.
- If you wish to discuss this further with me, please send me
an email at amanitiu@gmu.edu
- Office Hours
- by appointment, typically in the afternoon, from 2:00 pm on.
To make
sure I am available, please send an e-mail or call.
- Required Textbook
- Widrow and Stearns, Adaptive Signal Processing,
Prentice Hall 1985
- Recommended
- The Student Edition of MATLAB, V. 5.1 or higher.
- Simon Haykin, Adaptive Filter Theory, Third Edition,
Prentice Hall 1996
- Homework Excercises and Project
- HW will be assigned periodically and are due the following week
at the beginning of class.
- In the second part of the course students will develop
individual projects to be presented 2 weeks before the end of the
semester.
- Typically, a project may be a computational investigation
of selected adaptive algorithms published in recent technical
literature. Students should start planning such a project early in the
semester, by studying papers on adaptive signal processing and
proposing the project before the Spring Break.
