ECE 563 - Information Theory

Semesters Offered

TitleRubricSectionCRNTypeHoursTimesDaysLocationInstructor
Information TheoryECE563A37140DIS1230 - 1350 T R  2015 ECE Building Pramod Viswanath

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 Director

Description

Mathematical models for channels and sources; entropy, information, data compression, channel capacity, Shannon's theorems, rate-distortion theory.

Notes

Same as: CS 578 and STAT 563

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

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