Representation and analysis of random signals





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Course Contents

Review of probability, random variables, random processes; representation of narrow band signals. Transmission of signals through LTI systems; Estimation and detection with random sequences; BAYES, MMSE, MAP, ML schemes. KL and sampling theorem representations, matched filter, ambiguity functions, Markov sequences, linear stochastic dynamical systems. 


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