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Unit information: Symbols, Patterns and Signals in 2018/19

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Unit name Symbols, Patterns and Signals
Unit code COMS21202
Credit points 20
Level of study I/5
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Professor. Damen
Open unit status Not open

COMS10003, or EMAT10704



School/department Department of Computer Science
Faculty Faculty of Engineering

Description including Unit Aims

This unit seeks to acquaint you with the fundamental aspects of processing digital data, presented in the context of concrete examples from applications in computer vision, graphics, speech, audio, machine learning and data mining. Particular emphasis is placed on the importance of representation and modelling.

Intended Learning Outcomes

On successful completion of this unit, you will: understand how audio, video, graphical objects, etc are represented digitally; appreciate the role of representation, feature extraction, modelling, estimation, classification and clustering in digital data processing; appreciate the differences and commonalities between data processing tasks; understand the role of training/learning in modelling, classifying and clustering; be comfortable with high-dimensional spaces and associated transformations; be able to analyse data processing problems and decide what techniques to apply; understand how to manipulate and synthesise data, including 2D and 3D visualisation;

Teaching Information

36 hours for lectures, 24 hours of laboratory sessions. A further 140 hours are nominally set aside for coursework, private study, etc.

Assessment Information

60% exam, 1 piece of coursework 15%, 1 piece of coursework 25%

Reading and References

Course notes will be provided at the start of the lectures. The following book contains material for advanced study. Richard Duda, Peter Hart, David Stork. Pattern Classification. Second edition, 2000. John Wiley and Sons. ISBN: 0-471-05669-3 Recommended