|Assessment Type||Assessment length / details||Proportion|
|Semester Exam||2 Hours Exam||100%|
|Supplementary Exam||2 Hours Exam||100%|
On successful completion of this module students should be able to:
State various concepts of information and entropy and explain the relationships between
Achieve efficient data compression by coding procedures, guided by theoretical limits.
Explain the notion of a channel as a model of information transmission.
State Shannon’s main theorems about channel capacity and coding.
Reproduce the main assumptions and arguments leading to these theorems
Apply the theoretical results to construct and to analyse a variety of important channels.
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.
• 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
|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.|
This module is at CQFW Level 6