EE 631: Detection & Estimation Theory
Instructor: Dr. M. Soumekh
Office: 220 Davis Hall; Office Hours: By appointment; Email: firstname.lastname@example.org
Teaching Assistant: Ravi Kadlimatti
Office Hours: Mon 3:00-4:30 pm/by appointment at 235 Davis Hall; Email: email@example.com
Class Hours: Monday
5:00pm-7:20pm at 104 Knox
Final Exam on December 3rd, 2012
l Text Book
H. Van Trees, Detection, Estimation and Modulation Theory, part I, Wiley.
1. Wozencraft and Jacobs, Principles of Communication Engineering.
2. Proakis, Digital Communications.
3. Sage and Melsa, Estimation Theory with Applications to Communications and Control.
4. Ferguson, Mathematical Statistics.
5. C. Rao, Elements of Statistical Inference.
l Tentative Schedule
1. Introduction to detection and estimation. Classical decision theory, M-ary and binary hypothesis. (Chapter One, 2.1, 2.2.1, 2.3)
2. Receiver operating characteristics, Bayes estimation, real parameter estimation. (2.2.2, 2.4.1, 2.4.2)
3. Multiple parameter estimation, composite hypotheses. (2.4.3, 2.5)
4. The general Gaussian problem, performance bounds. (2.6, 2.7)
5. Performance bounds. (2.7, 2.8)
6. Orthogonal representations, Karhunen-Loeve expansion and integral equations. (3.1-3.4.4)
7. Optimum linear time varying filters, eigenvalues and eigen functions, spectral decomposition, communications system models. (3.4.5-3.7, 4.1)
8. Detection in AWGN, linear estimation. (4.2)
9. Detection in NWGN, performance and solution techniques. (4.3)
10. Signals with unwanted parameters. (4.4)
l Lecture notes
l Midterm Exam
l Problem Solving Session notes
l Final Exam
Updated by Ravi Kadlimatti on 12/2/2012
The State University of New York at Buffalo