EL 606: Information Theory
Polytechnic University
This
is a graduate course designed to prepare students for graduate work in
communication theory, information theory, wireless communications,
error-control coding, data compression, image and signal processing. The course
covers Shannon's entropy, source coding and channel
capacity theorems, the Gaussian channel and multiple user information theory.
The students are expected to be familiar with
basic concepts of probability. An introductory graduate level
probability course is recommended.
- Instructor: Elza Erkip , LC 225, elza@poly.edu
- Prerequisite: An
undergraduate course on probability is required. A graduate course on
stochastic processes might be helpful, but not required.
- Grading: Weekly
homeworks 30%, midterm 30%, final 40%.
- Required text: T. M.
Cover and J. Thomas, Elements of Information Theory, Wiley, 1991.
- Syllabus
Last modified May 21, 2002.