Understand fundamental concepts in modern Detection and Estimation theory including sufficiency, completeness; Neyman-Pearson and Bayes detector; maximum likelihood, Bayes, minimum mean square, and linear estimation; Kalman filters.

Apply these concepts to selected problems.