EG 6308 Random Variables and Stochastic Processes - 3 semester hours
Introduction to the underlying theory of stochastic processes. Topics include: Random sequences and convergence; autocorrelation, autocovariance, stationarity, ergodicity; stochastic calculus (continuity, differentiability, integrability); Poisson process; white-noise process; Gaussian process; random walk, Brownian motion, Wiener process; Markov chains; Markov processes; linear systems driven by random inputs