Introduction to Stochastic Processes

Catalog description

Elements of stochastic processes, discrete-time and continuous-time Markov chains, random walks, branching processes, birth and death processes, and Poisson point processes. Applications to queues and stochastic networks, resource management, biology, and physics. May include optimal stopping, hidden Markov models, renewal processes, martingales, Brownian motion, and Gaussian processes. Prerequisite(s): for undergraduates / Enrollment requirement for graduate students: MATH 374 , MATH 430 , and either MATH 440 or MATH 441 with grades of C (2.0) or better.