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EE 631: Detection & Estimation Theory

Fall 2012


Instructor: Dr. M. Soumekh

Office: 220 Davis Hall; Office Hours: By appointment; Email:


Teaching Assistant: Ravi Kadlimatti

Office Hours:  Mon 3:00-4:30 pm/by appointment at 235 Davis Hall; Email:


Class Hours: Monday 5:00pm-7:20pm at 104 Knox


       Final Exam on December 3rd, 2012

Course Syllabus

l  Text Book

H. Van Trees, Detection, Estimation and Modulation Theory, part I, Wiley.


l  References

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

Lecture 1         Lecture 2 Lecture 3 Lecture 4 Lecture 5 Lecture 6 Lecture 7

l  Midterm Exam

Question Paper         Solution

l  Problem Solving Session notes

Session 1        Session 2        Session 3       Session 4       Session 5

l  Final Exam

Question Paper         Solution

Updated by Ravi Kadlimatti on 12/2/2012

The State University of New York at Buffalo