EE626A - Topics in stochastic processes
Prerequisites:
3-0-0-9
Course Contents
Martingale convergence theorem, stopping times, sequential analysis. Ergodic Theory: Measure preserving transformations, stationary processes, mixing conditions, ergodic theorem, Shannon Millan Breiman theorem. Markov chains asymptotic stationarity, in decomposability, ergodicity. Continuous time processes: Separability, continuity, measurability, stochastic integral.
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