MATH 588 - Stochastic Analysis

Units: 3
Three hours lecture per week
Prerequisite(s): Admission to the Computer Science or Mathematics Graduate Program
Topics include: Brownian motion, stochastic integrals, conditional expectation, Kolmogorv’s Theorem, applications of Lebesgue Dominated Convergence Theorem. Introduction to Stochastic Differential Equations will be given.