Unit name | Intelligent Adaptive Systems (UWE) |
---|---|
Unit code | EMATM0034 |
Credit points | 15 |
Level of study | M/7 |
Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
Unit director | Professor. Dogramadzi |
Open unit status | Not open |
Pre-requisites |
None |
Co-requisites |
None |
School/department | School of Engineering Mathematics and Technology |
Faculty | Faculty of Engineering |
This unit (UFME7K-15-M) will be delivered at the University of the West of England (UWE)
This module focuses on intelligent control techniques. See https://secure.uwe.ac.uk/fet/uwedocs/modules/ (UWE login required) for full details.
Upon successful completion of this module students will be able to:
Lectures will introduce the fundamental concepts. Tutorial sessions will be used for two purposes: they will be used to expose students to demonstrations of the basic architectures in action as well as to discuss real implementations of these new techniques. Tutorials are designed to illustrate the essential details of a particular concept or technique, and especially its strengths and weaknesses in both technical and business contexts. At all times specific examples will be used to "ground" the theory.
End of module examination (50%, “Component A”) to assess individual abilities on problem analysis and subject knowledge.
One coursework assignment (50%, “Component B”) that assesses practical design and implementation abilities and understanding of a chosen topic from the syllabus.
The following list is offered to provide an indication of the type and level of information students may be expected to consult. As such, its currency may wane during the life span of the module specification. However, CURRENT advice on readings will be available via other more frequently updated mechanisms.
Nie & Linkens (1995) Fuzzy-Neural Control: Principles, Algorithms and Applications. Prentice Hall. [ISBN: 0133379167]
White & Sofge (1992) The Handbook of Intelligent Control. Van Nostrand-Reinhold.
Beal, R & Jackson, T (1991) Neural Computing - an introduction. Adam Hilger.
Raúl Rojas (1991). Neural Networks. A Systematic Introduction. Springer. Berlin
Brown & Harris (1994) Neurofuzzy Adaptive Modelling and Control. Prentice Hall. [ISBN: 0131344536]
A.E. Eiben and J.E. Smith (2003), Introduction to Evolutionary Computing, Springer
Miller, Sutton & Werbos (1991) Neural Networks for Control. MIT Press.
Arbib, M.A (1995) The Handbook of Brain Theory and Neural Networks. MIT Press.
Design tool user manuals e.g. MATLAB Fuzzy, Neural Network, and Simulink Toolboxes.