EE Department University of Nevada, Reno

Spring 2005

EE 791P Topics in Signal Processing: Signal Detection (3 Cr. Hrs.)

Prerequisites: EE 381 Signals and Systems, Math 352 Probability and Statistics

Instructor: Dr. M. S. Fadali, SEM 325

Time & Location: MW 11-12:15, SEM 344

Office Hours: M, W 2-3, T 10-11 (or by appointment)

Grading: 50% Assignments, 50% Project and presentations

Project: A research project based the published literature is required. The project may include a lab component.

Disability Statement

If you have a disability for which you need academic adjustments or accommodations, please contact me or Mary Zabel at the Disability Resource Center (Thomson Student Services - 107), as soon as possible to arrange for appropriate accommodations.

Prerequisites by Topic:

1. Probability and statistics.

2. Matrix algebra.

3. State-space equations (basics).

Text: R. D. Hippenstiel, Detection Theory: Applications and Digital Signal Processing, CRC Press, Boca Raton, 2001.

References:

1. R. N. McDonough & A. D. Whalen, Detection of Signals in Noise, Academic Press, San Diego, 1995.

2. H. L. Van Trees,Detection, Estimation, and Modulation Theory, Part III, J. Wiley, NY, 1971.

3. A. Papoulis, Probability, Random Variables, and Stochastic Processes, 4^th Ed., McGraw Hill, NY, 2002

Journals (include):

IEEE Trans. Signal Processing, IEEE Trans. Communication, IEEE Trans. Acoustics Speech Signal Processing, IEEE Trans. Automatic Control, Automatica, International J. Control.

Course Breakdown:

Topic	Chapter	Weeks
Introduction	1	0.5
Review of Probability Theory.	2, Notes	1
Random Signals	Notes	1
Hypothesis Testing	4	3
Detection of Known Signals in WGN	Handout	2
Detection of Signals with Random Parameters	Handout	1
Statistical Decision Theory	Handout	2
Applications	Papers	3
Total		14.5