KOM 505E - Probability Theory&Stochast.Pr

Course Objectives

1) Teaching probability theory
2) Teaching stochastic processes
3) Providing a solid foundation for other courses involving probabilistic applications

Course Description

Counting, elementary set theory, probability axioms, conditional probability, independence, discrete random variables, pmf, continuous random variables, cdf, pdf, moments, conditional distributions, functions of random variables, multiple random variables, jointly Gaussian vectors, probabilistic inequalities, laws of large numbers, central limit theorem, characteristic function, generating function and transform methods, stochastic processes, discrete-time processes, mean, auto-correlation, stationarity, cross-correlation, Poisson, Markov, Gaussian and Wiener processes, power spectral density, ergodicity, response of linear systems to random signals