IE 410 - Stochastic Processes and Their Applications
Modeling and analysis of stochastic processes. Background on probability models. Transient and steady-state behavior of discrete-time Markov chains. Time-reversible Markov chains, Markov decision processes. Applications of Markov chains. Branching processes. Homogeneous and inhomogeneous Poisson processes. Selected topics. Same as CS 481. 3 undergraduate hours. 4 graduate hours. Prerequisite: IE 310.