Stochastic Processes
Course Name: Stochastic Processes
Workload: 72 class hours
Summary: Probability theory review. Discrete random variables (DRV). Expected values of DRVs. Multiple DRVs. Continuous random variables (CRV). Expected values of CRVs. Multiple CRVs. CRV sequence convergence. Law of large numbers. Central limit theorem. Random processes. Types of processes. Stationarity. Stationary processes in the broad sense. Autocorrelation sequence. Power spectral density. Response of linear systems to stationary processes in the broad sense. Gaussian random processes. Poisson process. Markov Chains.
