Fuzzy ART with Group Learning
Haruka Isawa, Masato Tomita, Haruna Matsushita, Yoshifumi Nishio · 2006
Abstract — Adaptive Resonance Theory (ART) is an unsuper-vised neural network based on competitive learning which is capable of learning stable recognition categories in response to arbitrary input sequences. In this study, we propose an application step, called “Group Learning”, for Fuzzy ART in order to obtain more effective categorization. This new algorithm is called Fuzzy ART with Group Learning (Fuzzy ART-GL). The important feature of the group learning is that creating a connection between similar categories. We investigate the behavior of Fuzzy ART-GL with application to the recognition problems. I.