EEC 650 - Signal Detection & Estimation

(4 credits)

Prerequisite(s): closed to non degree grads, all undergrads and grads who are not in the college of engineering Prerequisite: EEC 512. The classical theory of detection and estimation of signals in noise. Bayesian hypothesis testing, minimax hypothesis testing, Neyman-Pearson hypothesis testing, composite hypothesis testing, signal detection in discrete time, sequential detection. Nonparametric and robust detection parameter estimation, Bayesian estimation, maximum likelihood estimation, Kalman-Bucy filtering, linear estimation, Wiener-Kolmogorov filtering, applications to communications.

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