Fuzzy & Neural Pattern Recognition /5 Videotapes (Book)

This course covers two technologies: fuzzy models and computational neural networks. It provides information on how both are used in selected pattern recognition applications. Fuzzy sets were introduced by Zadeh in 1965 to represent/manipulate data and information possessing non-statistical uncertainties. Computational neural networks were first discussed by McCullogh and Pitts in 1943 as a means of imitating the power of biological systems for data and information processing. This video course provides an overview of the major considerations, models and algorithms that can be used for feature analysis, clustering and classifier design. Particular emphasis will be placed on proven methods for applications and system development.