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