Information Theory

Module Identifier
MA35810
Module Title
Information Theory
Academic Year
2026/2027
Semester
Semester 1
Co-ordinator
Dr Rolf Gohm
Reading List
View on Aspire
Pre-Requisite
MA26010
Exclusive (Any Acad Year)
MAM5820
Other Staff
Dr Rolf Gohm

Assessment

Assessment Type

Assessment details

Assessment length

Proportion
Semester Exam Exam: 2 Hours 100%
Supplementary Exam Exam: 2 Hours 100%

Learning Outcomes

On successful completion of this module students should be able to:

  1. State various concepts of information and entropy and explain the relationships between them.
  2. Achieve efficient data compression by coding procedures, guided by theoretical limits.
  3. Explain the notion of a channel as a model of information transmission.
  4. State Shannon’s main theorems about channel capacity and coding.
  5. Reproduce the main assumptions and arguments leading to these theorems
  6. Apply the theoretical results to construct and to analyse a variety of important channels.

Brief description

C. Shannon’s seminal paper ‘A mathematical theory of communication’ (1948) created information theory as a part of mathematics. It provides the tools for a rigorous understanding of information processing and communication. In this module we carefully develop the main concepts like entropy, data compression and coding, channels and their capacity. We explain the main theorems and results and apply them to various classes of examples.

Content

• Introduction, history, what is information, examples
• Entropy, joint and conditional entropy, relative entropy and mutual information, rules and inequalities
• Asymptotic equipartition property, typical sets and source coding
• Data compression, Kraft inequality and optimal codes, Huffman codes
• Channels and channel capacity, examples
• Shannon’s channel coding theorem, zero error codes, Hamming codes
• Source-channel coding theorem, binary case
• Information transmission guided by theory, detailed discussion of examples

Module skills

Skills type

Skills details
Adaptability and resilience Good understanding of the contents requires considerable intellectual effort over an extended period of time.
Co-ordinating with others Discussing the theory and solving problems together during the module is encouraged.
Creative Problem Solving Problem sessions based on problem sheets to be solved independently. This is crucial to prepare for the problems in the exam.
Critical and analytical thinking Theory is developed rigorously and compared with real world situations
Digital capability Insights are provided into the mathematical principles of digital information processing.
Professional communication Discussing the theory and solving problems together during the module is encouraged.
Real world sense Theory is compared with real world applications.
Reflection Intuitive ideas need to be translated into mathematical reasoning.
Subject Specific Skills The ability to solve concrete problems in information theory is checked in the exam.

Notes

This module is at CQFW Level 6