EE4-07 Coding Theory
Lecturer(s): Dr Wei DaiAims:
The goal of this course is to cover basic knowledge on error correcting codes and finite fields, and to expose the connection between coding theory and other engineering topics.
There is no required textbook. The lecture notes will provide all the necessary definitions and information. The main prerequisite is mathematical maturity. The students are expected to be familiar with linear spaces and elementary probability. The materials are theoretical. Motivation and commitment are highly appreciated.
Learning Outcomes:
Understand several popular error correcting codes.
Understand basic mathematical backgrounds on finite fields which pave the way for further study of more sophisticated error correcting codes.
Understand how coding theory and tools are connected to machine learning, signal processing, and security (if time allows to cover advanced topics).
Syllabus:
Elementary ideas of redundancy. Fundamental problems in coding theory and practice. Distance measures. Bounds to the performance of codes. Important linear codes, e.g. Hamming codes. Construction and properties of finite fields. Cyclic, BCH and Reed Solomon codes. When time allows, we will choose some of the following topics to cover: convolutional codes and Viterbi decoding, LDPC codes and belief propagation, error correcting over real field, and coding for security.
Assessment:
One 3-hour exam in April/May
Coursework contribution: 0%
Term: Autumn
Closed or Open Book (end of year exam): Closed
Coursework Requirement
nil
Oral Exam Required (as final assessment): N/A
Prerequisite: None required
Course Homepage: To be announced.
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