18-752 Detection, Estimation, and Identification

(12 Units, taught everyother spring semester, next offering Spring 2005, graduate course, satisfies ECE coverage requirements) Basic graduate course in detection and estimation theory. Decision theory: Binary hypothesis testing, M-ary testing, Bayes, Neyman-Pearson, Min-Max. Performance. Probability of error, ROC. Estimation theory: linear and nonlinear estimation, parameter estimation. Bayes, MAP, maximum likelihood, Cramér-Rao bounds. Bias, efficiency, consistency. Asymptotic properties of estimators. Orthogonal decomposition of random processes and harmonic representation. Waveform detection and estimation. Wiener filtering and Kalman-Bucy filtering. Elements of identification. Recursive algorithms. Spectral estimation. Topics may vary. 4 hrs. lec. Prerequisite: 18-751.