EL 606: Information Theory
Polytechnic University, Fall 2004
This is a graduate course designed to prepare students for graduate work in communication theory,
information theory, wireless communications, errorcontrol 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.
 Instructor:
Emina Soljanin
 Prerequisite: Knowledge of probability at undergraduate level is required.
An introductory graduate level probability course is recommended.
 Grading:
homework assigned biweekly 30%, midterm 30%, and final 40%.

Required text: T. M. Cover and J. Thomas, Elements of Information Theory,
Willey, 1991.

Recommended literature:

C. E. Shannon, ``A mathematical theory of communication,''
Bell System Technical Journal, vol. 27, pp. 379423 and
623656, July and October, 1948.
download

Class material:

Lectures: Syllabus, Lecture 2,
Lecture 5,

Homeworks: HW1, HW2,
HW3, HW4, HW5, HW6,
HW8, HW9, HW10.

Homework Solutions: HW1S, HW2S,
HW3S, HW4S, HW5S,
HW6S, HW8S,
HW9S, HW10S.

Tests: Midterm with solutions,
Final with solutions.