Information Theory

  • Class 45
  • Practice 15
  • Independent work 60
Total 120

Course title

Information Theory

Lecture type


Course code






Lecturers and associates

Course objectives

Information theory history and importance; Symbol, message, information, communication.
Discrete communication system, probabilistic view and information measures.
Entropy, noiseless coding theorem; Mutual information.
Information sources .
Types of codes; Optimal code; Entropy coding.
Entropy coding.
Entropy coding; Lossy coding.
Midterm exam.
Error detecting and correcting codes, block codes.
Hamming distance, code equivalence, perfect codes.
Binary linear block codes, generating matrix, parity check matrix, syndrom.
Types of binary linear block codes.
Convolutional and turbo coding.
Channel capacity, noisy-channel coding theorem.
Final exam.

Prerequisites for:

  1. Information, Logic and Languages
  2. Public Mobile Network
  3. Introduction to Virtual Environments

Required reading

Igor S. Pandžić et al. (2009.), Uvod u teoriju informacije i kodiranje, Element
Željko Ilić, Alen Bažant, Tomaž Beriša (2014.), Teorija informacije i kodiranje, Element
Roberto Togneri, Christopher J.S deSilva (2003.), Fundamentals of Information Theory and Coding Design, CRC Press

Minimal learning outcomes

  • Identify information, coding and communication problems
  • Explain coding and compression methods and information limits
  • Apply accepted knowledge to real systems analysis
  • Analyze complex information and communication systems
  • Explain phenomens in different areas of science
  • Estimate performances of different information and communication systems
  • Apply techniques of entropy and error correcting codes
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