The main objective of this course is to introduce the principles of statistical detection and estimation theory to the students. In this context, detection of both deterministic and random signals will be studied. Using approaches like Bayesian and maximum likelihood, parameter estimation from noisy signals will be realized.

Hypothesis testing: Bayesian, minimax and Neyman-Pearson approaches, Detection of deterministic and random signals, General Minimum Variance Unbiased Estimation, Cramer Rao Lower Bound, Maximum likelihood estimation.