Semester I includes an introduction to probability spaces and random variables, the theory of countable state Markov chains and renewable processes, laws of large numbers and the central limit theorems. Semester II provides a rigorous mathematical foundation to probability theory and covers conditional probabilities and expectations, limit theorems for sums of random variables. Stochastic Processes Topics in the theory on continuous parameter stochastic processes. The topic of the course in 1995-96 is stochastic recursive algorithms. Computer Vision-The Analysis of Visual Signals.
Topics vary from year to year.
Topics vary from year to year. Return to Top of Page Engineering Graduate Courses Attention is drawn to the following courses in the Division of Engineering . Linear Systems Theory Modeling physical systems by transfer matrices as well as state-space and differential operator equations. Applications of linear algebra and polynomial matrix theory. Equivalence of alternative system representations and state transition matrix determination.