ECE 730 Modern Probability Theory and Stochastic Processes, Lec. 1, Spring 2009

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

Credits:        3

Prerequisites:  ECE 331 or equiv.

Class Meets:    MWF 2345 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.  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.

Textbook:       Required: Probability and Random Processes for
                          Electrical and Computer Engineers,
                          J. A. Gubner, Cambridge University Press, 2006.
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Computer Usage: Some homework assignments may require MATLAB.

Papers:         None.

Projects:       None.

Grading Policy: Homework   10%,  No late homework accepted.
                Midterm    40%
                Final Exam 50%