ECE 563
Information Theory

Displaying course information from Fall 2013.

Section Type Times Days Location Instructor
A DIS 1230 - 1350 T R   245 Everitt Lab  Yihong Wu
Web Page http://courses.engr.illinois.edu/ece563
Official Description Mathematical models for channels and sources; entropy, information, data compression, channel capacity, Shannon's theorems, and rate-distortion theory. Course Information: Prerequisite: One of ECE 534, MATH 464, MATH 564.
Subject Area Communications
Course Prerequisites Credit in MATH 464 or MATH 564 or ECE 534
Course Directors Richard E Blahut
Detailed Description and Outline

Topics:

  • Entropy, relative entropy, mutual information
  • Asymptotic equipartition property
  • Entropy rates of a stochastic process
  • Lossless data compression (Huffman, Ziv-Lempel, Arithmetic, Shannon-Fano codes): Kraft inequality, Shannon's source coding theorem
  • Channel capacity: jointly typical sequences, Fano's inequality, Shannon's channel coding theorem and its converse
  • Differential entropy
  • Gaussian channels
  • Rate-distortion theory: Shannon's source coding theorem relative to a fidelity criterion

Same as: CS 578 and STAT 563

Texts
T. Cover and J. Thomas, Elements of Information Theory, Wiley, 1991.
Last updated: 2/13/2013