Stochastic Processes Comm/ctrl

ECSE-6550

Review of measure and integration theory, elements of probability, random variables, conditional probability, and expectations. Stochastic processes, stationarity, and ergodicity. Gaussian processes and Brownian motion, the Poisson process. Markov processes, wide-sense stationary processes, spectral representations, linear prediction and filtering. Stochastic integrals and differential equations, white noise and the stochastic calculus, the Fokker-Planck equation, diffusion processes, recursive filtering and estimation, evaluation of likelihood ratios. Applications in communication, information processing, and control.

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