STOCHASTIC SIGNALS AND NOISE

Section

Professor

Predrag Jelenkovic

Course Information

Prerequisite: Stat.-IEOR W3658 or the equivalent. Characterization and specification of stochastic processes as models of signal ensembles. Stationarity and ergodicity; correlation functions and power spectra. Wiener, Poisson, Markov, Gaussian processes, shot noise, Markov chains. Random signals and noise in linear and nonlinear systems; linear and nonlinear transformations of random processes. Orthogonal series representation of signals. Applications to communication, control, filtering, and prediction.

Department: Electrical Engineering(ELEN)

Subject: Electrical Engineering(ELEN)

School: Fu Foundation School of Engineering and Applied Science

Division: School of Engineering and Applied Science: Graduate

Course ID: 6711