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COMP4231: DATA COMPRESSION AND CODING THEORY

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Type	Open
Level	4
Credits	20
Availability	Not available in 2024/2025
Module Cap	None.
Location	Durham
Department	Computer Science

Prerequisites

COMP3731 Cryptography

Corequisites

None

Excluded Combinations of Modules

None

Aims

To understand:
the main techniques for error correction
the key results of information theory and their relevance to cryptography and data compression
the main techniques for lossless and lossy date compression
the efficiency criteria for data compression.

Content

Linear error correcting codes, including Hamming codes
Bounds on codes
Cyclic codes, including Reed-Solomon codes and their decoding
Code-based cryptography
Channel capacity and rate-distortion theory
Information-theoretic security
Huffman coding
Arithmetic coding
Lempel-Ziv and application to ZIP or PNG
Context-based compression o Transform domain compression with application to JPEG
Wavelet-based compression with application to JPEG2000
Video and Audio compression

Learning Outcomes

Subject-specific Knowledge:

On completion of the module, students will be able to demonstrate:
an understanding of the key features of error-correcting codes
an understanding of public-key cryptosystems based on error-correcting codes
an understanding of the how information theory describes the limits of data compression and cryptography
an understanding of the key features of popular lossy and lossless compression techniques
an understanding of the performance criteria for lossless and lossy compression

Subject-specific Skills:

On completion of the module, students will be able to demonstrate:
an ability to assess the performance of error-correcting codes an ability to assess the effectiveness and security of code-based cryptosystems
an ability to use information-theoretic tools to bound the performance of digital communication systems
an ability to assess and design compression techniques for diverse kinds of data
an ability to implement the key tools used in data compression.

Key Skills:

On completion of the module, students will be able to demonstrate:
an ability to use algebraic techniques to solve communication problems
an ability to apply information theory to related domains
an ability to identify and assess the quality of heuristics for different algorithms

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

Lectures enable the students to learn new material.
The examination assesses the knowledge and understanding of the material covered in the lectures.

Teaching Methods and Learning Hours

Activity	Number	Frequency	Duration	Total
lectures	42	2 per week	1 hour	42
preparation and reading				158
Total				200

Summative Assessment

Component: Coursework		Component Weighting: 50%
Element	Length / Duration	Element Weighting	Resit Opportunity
Summative Assignment		100	No

Component: Examination		Component Weighting: 50%
Element	Length / Duration	Element Weighting	Resit Opportunity
Examination	2 hours	100	No

Formative Assessment

Example formative exercises are given during the course.

More information

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