EE 381J: Probability and Stochastic Processes I

Probability spaces, random variables, expectation, conditional expectation, stochastic convergence, characteristic functions, and limit theorems. Introduction to Markov and Gaussian processes, stationary processes, spectral representation, ergodicity, renewal processes, martingales, and applications to estimation, prediction, and queueing theory.

Course Level: 

Graduate

Prerequisites: 

Graduate standing, and Electrical Engineering 351K or the equivalent.