107.A23 Information- and Coding Theory
This course is in all assigned curricula part of the STEOP.
This course is in at least 1 assigned curriculum part of the STEOP.

2021S, UE, 1.0h, 2.0EC

Properties

  • Semester hours: 1.0
  • Credits: 2.0
  • Type: UE Exercise
  • Format: Online

Learning outcomes

After successful completion of the course, students are able to...

  • define and compute maximal und mean uncertainty
  • cite and apply Kraft's inequality
  • define and compute entropy, relative entropy, conditional entropy, information
  • state properties of entropy
  • define information sources
  • cite and apply the Shannon-McMillan-Breiman theorem
  • define codes
  • define and check decipherabilty of codes
  • state theoretical limits of data compression
  • define and construct Huffman-, Shannon-, Fano- and arithmetic codes
  • define channels and their capacity
  • define Hamming distance
  • define minimal distance of a code, error detecting and error correcting codes
  • define and construct linear codes

Subject of course

cf. VO 107.A18

Teaching methods

Problems to be solved by students

Mode of examination

Immanent

Lecturers

Institute

Examination modalities

Presentation of solutions

Course registration

Begin End Deregistration end
27.02.2021 11:00 27.03.2021 00:00 27.03.2021 00:00

Group Registration

GroupRegistration FromTo
Informationstheorie27.02.2021 11:0027.03.2021 00:00

Curricula

Study CodeObligationSemesterPrecon.Info
033 201 Technical Mathematics Mandatory elective

Literature

No lecture notes are available.

Miscellaneous

Language

if required in English