ECE 730 Modern Probability Theory and Stochastic Processes, Lec. 1, Fall 2002

Instructor:     John A. Gubner, Associate Professor, ECE Department.
                Office: 3615 Engr. Hall.
                Phone: 263-1471.
                E-mail: gubner@engr.wisc.edu
                Homepage: http://www.cae.wisc.edu/~gubner/

Credits:        3

Prerequisites:  ECE 331 or equiv.

Class Meets:    MWF 1:20-2:10 in 2535 Engr. Hall

Goals & Topics: This is a second course in probability and random processes.
                After a quick review of some key topics from ECE 331, we
		begin with a study of random vectors, with emphasis on the
		multivariate Gaussian.  Complex-valued Gaussian random vectors
		are also covered.  We then introduce the Poisson process and
		the Wiener process (a.k.a. Brownian motion), including the
		Wiener integral.  Convergence of random variables
		(in mean of order p, in probability, in distribution,
		and almost surely) is covered.  Markov chains in discrete
		and continuous time are introduced.

Course Notes:   Required, available at Bob's Copy Shop.

Computer Usage: Some homework assignments may require MATLAB.

Papers:         None.

Projects:       None.

Grading Policy: Homework   10%,  No late homework accepted.
                Exam 1     40%
                Exam 2     50%