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227-0417-00L 6 Credits BSC , DS , DR , MSC D-USYS , D-BAUG , D-MAVT , D-INFK , D-MTEC , D-MATH , D-BIOL , D-GESS , D-ITET , D-ARCH , D-CHAB
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Applied Digital Information Theory I

Lecturers & Examiners: Prof. Dr. Amos Lapidoth
VVZ CR 4.0

Last Updated: 2026-02-05 15:14:58

Abstract

This course covers the basic concepts of information theory and of communication theory. Topics covered include the entropy rate of a source, mutual information, typical sequences, the asymptotic equi-partition property, Huffman coding, channel capacity, the channel coding theorem, the source-channel separation theorem, and feedback capacity.

Objective

The fundamentals of Information Theory including Shannon's source coding and channel coding theorems

Content

The entropy rate of a source, Typical sequences, the asymptotic equi-partition property, the source coding theorem, Huffman coding, Arithmetic coding, channel capacity, the channel coding theorem, the source-channel separation theorem, feedback capacity

Resources

Literature

T.M. Cover and J. Thomas, Elements of Information Theory.

General Information

Language
English
Levels
BSC , DS , DR , MSC
Frequency
Yearly recurring

Examination

Type
session examination
Mode
oral 30 minutes

Course Components

Type Title Time & Place Hours
lecture with exercise Applied Digital Information Theory I
  • Wed 13:15-17:00 (ETZ E 8)
4 h weekly

Offered In