Neural Network and Fuzzy Logic System
Course Code: CSE 6025
Course Type: n/a
Credit: 3.00
Credit Hour: 3.00
Prerequisite: n/a
Fundamentals of Neural Networks,
Back propagation and related training algorithms; Hebbian learning;
Cohen-Grossberg learning; The BAM and Hopfield memory; simulated Annealing;
Different types of neural networks; Counter propagation, probabilistic, radial
basic function, generalized regression etc. Adaptive Resonance theory; Dynamic
systems and neural control; The Boltzman machine; Self organizing maps;
spatiotemporal pattern classification, The Neo-cognition, practical aspects of
neural networks.
Introduction, crisp sets to fuzzy
sets; Operations on fuzzy sets, fuzzy arithmetic, fuzzy relations and fuzzy
relation equations; Fuzzy logic, fuzzy propositions and quantifiers, linguistic
hedges, implications; Applications: Expert systems, fuzzy controllers, pattern
recognition and information retrieval systems, engineering applications,
medical applications.
|
