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  • 12:42 AM, Friday, 29 Mar 2024


Course Postgraduate
Semester Sem. II
Subject Code AVD621
Subject Title Estimation and Detection Theory

Syllabus

Estimation Theory, Maximum Likelihood estimation (MLE): exact and approximate methods (EM, alternating max, etc), Cramer ‐ Rao lower bound (CRLB), Minimum variance unbiased estimation, Sufficient Statistics, Best Linear Unbiased Estimation, Large and Small Sample Properties of Estimators, Bayesian Inference and Estimation - MMSE, MAP Estimation, Wiener and  Kalman filtering (sequential Bayes), Detection Theory: Likelihood Ratio testing, Bayes detectors, Minimax detectors, Multiple hypothesis tests Neyman ‐ Pearson detectors (matched filter, estimator ‐ correlator, etc), Wald sequential test, Generalized likelihood ratio tests (GLRTs), Wald and Rao scoring tests.

Assessment: The course will feature two midterms and a final exam. There will be continuous evaluation using class tests, problem sets, and programming assignments.

Text Books

Same as Reference

References
  1. Fundamentals of Statistical Signal Processing: Estimation Theory (Vol 1), Detection Theory (Vol 2), .M. Kay's, Prentice-Hall Signal Processing Series, 1993
  2. Linear Estimation, Kailath, Sayed and Hassibi, Prentice-Hall Information and Sciences Series, 1 st edition, 2000.
  3. Statistical Signal Processing (Paperback) by Louis Scharf, 1 st edition,
  4. An Introduction to Signal Detection and Estimation, Poor, H. Vincent, Springer Text in Electrical Engineering, 1994
  5. Detection, Estimation, and Modulation Theory –Part I, H.Van Trees, et.al, 2 nd edition, Wiley.
  6. Monte Carlo Strategies in Scientific Computing, J.S. Liu, Springer ‐ Verlag, 2001. Stochastic Simulation, B.D. Ripley, Wiley, 1987.