Course Catalogue

Information Theory UESTC5015

  • Academic Session: 2026-27
  • School: School of Engineering
  • Credits: 20
  • Level: Level 5 (SCQF level 11)
  • Typically Offered: Semester 1
  • Available to Visiting Students: No
  • Collaborative Online International Learning: No
  • Curriculum For Life: No

Short Description

Through the delivery of this course, students will develop a comprehensive understanding and mastery of the concepts, principles, and analytical methods of Information Theory.

Timetable

40 hours of lectures

Requirements of Entry

None

Excluded Courses

None

Co-requisites

None

Assessment

50% Final exam (open-book examination)

50% Continuous assessment

Main Assessment In: December

Course Aims

The course aims to enhance scientific thinking and logical reasoning skills, enabling students to effectively analyze and design advanced information and communication systems.

Intended Learning Outcomes of Course

By the end of this course students will be able to:

1. Calculate the entropy and differential entropy of Markov processes and n-fold extensions of discrete/continuous sources;

2. Describe asymptotic equipartition and the lossless compression coding theorem, evaluate the essential properties of Fano and Huffman codes and design useful Huffman codes.

3. Explain the concepts of noise entropy, noise differential entropy, average mutual information, and channel capacity for n-fold extended discrete/continuous channels;

4. Design effective Hamming codes for given communication channel problems, and explain the merits of modern low-density parity-check codes;

5. Summarise key concepts of lossy compression problems, including the fidelity criterion, test channel, and rate distortion function, and apply 13-segment A-law quantization code;

6. Extend the principles of information theory to discrete/continuous correlated sources and multiple-access channels using the distributed lossless compression coding theorem, distributed error correction coding theorem and superposition error correcting coding theorem.

Minimum Requirement for Award of Credits

No exceptions