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227-0420-00L 6 Credits BSC , DR , MSC D-ITET , D-MATH , D-INFK
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Information Theory II

VVZ CR n/a

Last Updated: 2026-06-01 11:33:15

Abstract

This course builds on Information Theory I. It introduces additional topics in single-user communication, connections between Information Theory and Statistics, and Network Information Theory.

Objective

The course's objective is to introduce the students to additional information measures and to equip them with the tools that are needed to conduct research in Information Theory as it relates to Communication Networks and to Statistics.

Content

Sanov's Theorem, Rényi entropy and guessing, differential entropy, maximum entropy, the Gaussian channel, the entropy-power inequality, the broadcast channel, the multiple-access channel, Slepian-Wolf coding, the Gelfand-Pinsker problem, and Fisher information.

Resources

Lecture Notes

n/a

Literature

T.M. Cover and J.A. Thomas, Elements of Information Theory, second edition, Wiley 2006

Learning Materials (Links)

General Information

Language
English
Levels
BSC , DR , MSC
Frequency
Every two years

Examination

Type
session examination
Mode
oral 30 minutes

Course Components

Type Title Time & Place Hours
lecture with exercise Information Theory II
  • Thu 14:15-18:00 (ETZ H 91)
4 h weekly

Offered In