Introduction to Information Theory

Department: 
MATH
Course Number: 
4280
Hours - Lecture: 
3
Hours - Lab: 
0
Hours - Recitation: 
0
Hours - Total Credit: 
3
Typical Scheduling: 
Every spring semester

The measurement and quantification of information. These ideas are applied to the probabilistic analysis of the transmission of information over a channel along which random distortion of the message occurs.

Prerequisites: 

MATH 3215 or MATH 3225 or MATH 3235 or MATH 3670 or MATH 3770 or ISyE 3770 or CEE 3700

Course Text: 

At the level of The Theory of Information and Coding, McEliece; or Information Theory, Ash

Topic Outline: 
  • Definitions: measure of uncertainty (entropy), measure of information, examples; input, output, and channel terminology
  • Fundamental Theorem of Information Theory for the discrete memoryless channel
  • Information sources, ergodicity, and the Shannon-McMillan Theorem. Examples and consequences
  • Other topics, for example error detecting and correcting codes, etc.