Table of Contents

E1 244: Detection and Estimation Theory

Logistics

Instructor: Chandra R. Murthy (cmurthy at ece)
Class hours: MWF 11am-12:30pm, Room L5 in the Central Lecture Hall Complex (near the GATE office).
TA: Bharath B. N. (bharath at ece)

Textbooks:
1. H. V. Poor, An Introduction to Signal Detection and Estimation, 2nd Ed., Springer-Verlag, 1994.
2. H. L. Van Trees, Detection, Estimation and Modulation Theory, Parts 1 and 2, John Wiley Inter-Science.
3. E. L. Lehman, Testing Statistical Hypothesis, John Wiley, 1986.
4. M. D. Srinath, P. K. Rajasekaran and R. Vishwanathan, An Introduction to Statistical Signal Processing with Applications, Prentice-Hall, 1996.
5. To review probability: A. Papoulis, Probability, random variables, and stochastic processes, McGraw-Hill International Edition.

Prerequisites: Random processes (E2-202 or equivalent).

Syllabus:

S. No. Topic Num. Lectures
1Background and probability review 2
2Bayesian, Neyman-Pearson & Minimax detection 2
3Composite hypothesis testing, Generalized LRT 1
4Sequential and distributed detection 2
5Performance analysis 1
6Nonparametric detection 1
7Signal detection in continuous time, KL theorem 1
8Detection in Gaussian noise 2
9Estimation theory: Bayesian, MMSE and MAP estimation 2
10Fischer-Neyman factorization theorem, Rao-Blackwell theorem 2
11Maximum-Likelihood estimation 2
12Exponential families and the Cramer-Rao Bound 2
13Consistency, efficiency and asymptotics 2
14Kalman filtering 2
15Linear estimation of signals, Weiner filtering 2
Total 26

Grading

Homeworks: 10%
Midterm 1: Feb. 12, 2010, in class: 25%. Click here for the solution. Thanks to Bharath for preparing the solution!
Midterm 2: Mar. 12, 2010, in class: 25%. Click here for the solution. Thanks to Prof. Srinivasan for help with preparing the test and the solution!
Final: Apr. 27, 2010, 9am - 12pm: 40%

Homeworks

Homeworks are posted here.

Announcements

  • The first class will be held on Jan 04, 2010 at EC 1.08
  • Slides from Dr. Vengadarajan and Prof. Srinivasan's classes are posted here.
  • Slides from Prof. Srinivasan's classes on the week of Mar. 15th are also posted here.
  • Notes on the EM algorithm are here.

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