Stochastic Processes: 3 semester hours

Catalog description

Probability overview, distribution and density functions, moments, time averaging and sampled averaging. Stochastic processes: Gaussian, Markov process, Poisson, Rice, Wiener-Levy processes, bi-model and tri-model processes. Modeling of systems using stochastic processes and system analysis. Karhunen-Loeve transform, bounds and their use in systems. Decision Rules: Maximum likelihood, Minimum Error, Kalman and Wiener filters, Linear and non-linear estimation and Optimization techniques.