EE 381K Information Theory - Fall 2002


Instructor

Description

This course discusses Shannon's Information Theory, including source and channel coding theorems, together with some more recent ideas, such as Kolmogorov complexity, network information theory, and connections with large deviations.

The course is intended to introduce the fundamental ideas in information theory to students interested in communications and systems. In addition, we will draw on some recent papers to touch on some recent ``hot''; topics in lecture or during your presentations: e.g., sending information streams through queues, complexity of simulation, role of priorities in transmission, rate distortion and variable rate compression. See outline for details.

Prerequisites

This course is intended for graduate students with a background in communications. A mandatory prerequisite for this course is a graduate course in Probability and Stochastic Processes , such as EE381J.

Required text

Elements of Information Theory , by Cover and Thomas. Wiley, 1991.

Format/Evaluation

Homework will be assigned weekly and will be due at the beginning of the last class in the following week. They will be graded on a {-, ok, + } basis, you will get solutions, and they will be worth a total of 30 pts. Yo may work in groups of 2-3, if so please turn in only 1 hwk paper with the group's name. There will be two in-class midterms worth 25 pts each. No final exam, but a (20 min) presentation worth 20 pts on a topic of your choice (subject to my approval) - attendance is mandatory.

Final Exam:

No final, however you will be required to select a topic and make a presentation to the class. Your time may be prior to final exams or before - attendance will be mandatory - Wednesday May 13, 9-12:00.

Where does course this fit in?

Prior to taking this course, you might consider taking: Probability and Stochastic Processes I this is a foundations graduate course and perhaps Digital Communications.. Some related courses are, Wireless Communications; Digital Signal Processing. Advanced Signal Processing.


Note: All departmental, college and university regulations concerning drops will be followed. The University of Texas at Austin provides upon request appropriate academic adjustments for qualified students with disabilities. For more information, contact the Office of the Dean of Students at 471-6259, 471-4241 TDD.