| Topics for this course will cover Detection: binary hypotheses, Bayes decision criteria, risk decision space, performance, MAP receivers, M-ary hypotheses; Estimation: Bayes estimation; MMSE, MAP, ML estimators, performance, Cramer-Rao inequality, efficient estimators, multiple parameters estimation; General Gaussian detection and estimation; Random process characterization: Karhunen – Loeve expansion, Gaussian process, white processes, Wave form communication: wave form detection, matched filter, performance, FSK, PSK, ASK waveform parameter estimation. Prerequisite: EE6513 . |
