Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence

Abstract

This work combines neural networks and fuzzy systems, presenting neural networks as trainable dynamical systems and developing mechanisms and principles of adaption, self-organization, convergence and global stability. It includes the new geometric theory of fuzzy sets, systems and associated memories, and shows how to apply fuzzy set theory to adaptive control and how to generate structured fuzzy systems with unsupervised neural techniques.