Autoassociative Memory Evolving System Based on Fuzzy Basis Functions

This paper proposes a neuro-fuzzy architecture of evolving autoassociative memory network. Learning of a given construction is based on fuzzy basis functions. The algorithm of membership functions centres determination is described and processes of fundamental memory patterns accumulation and their retrieval are considered. This hybrid neuro-fuzzy system combines advantages of artificial neural networks, fuzzy inference systems and evolving systems and its using allows researchers to increase autoassociative memory capacity without considerable complication of its construction.