CSE5301

Neuro-Fuzzy Computing

(IT)

6 points + 2 hours lectures + 2 hours lab/tutorial + first semester + Clayton campus + Prerequisites: MAT 1811/1812 or MAT 1841/1830 or equivalent, and 2 years or more of study in a computing related course

Synopsis: Theoretical background of fuzzy set, fuzzy logic and neural networks, applications in control, signal processing, image processing and communication networks. Topics include: fuzzy sets, fuzzy arithmetic and relations; fuzzy logic, membership functions; fuzzy inference and fuzzy systems; fuzzy logic controllers and predictors; fuzzy system applications in image processing, pattern recognition, communication networks and other areas; artificial neural network concepts; the perceptron and linear neural networks; multi-layer feedforward neural networks; self-organising systems, competitive learning, self-organising feature maps and recurrent neural networks.

Assessment: 50% reports and assignments + 50% final examination (2 hours)