Summary
2007 International Symposium on Nonlinear Theory and its Applications
2007
Session Number:18PM2-B
Session:
Number:18PM2-B-5
Fuzzy Adaptive Resonance Theory with Group Learning and its Applications
Haruka Isawa, Masato Tomita, Haruna Matsushita, Yoshifumi Nishio,
pp.292-295
Publication Date:2007/9/16
Online ISSN:2188-5079
DOI:10.34385/proc.41.18PM2-B-5
Summary:
Adaptive Resonance Theory (ART) is an unsupervised neural network based on competitive learning which is capable of automatically finding categories and creating new ones. Fuzzy ART is a variation of ART, allows both binary and continuous input pattern. In this study, we propose an additional step, called "Group Learning", for the Fuzzy ART in order to obtain more e?ective categorization. This algorithm is called Fuzzy ART with Group Learning (Fuzzy ART-GL). The important feature of the group learning is that creating connections between similar categories. In other words, the Fuzzy ART-GL learns not only categories but also its connections, namely, groups of the categories. We investigate the behavior of Fuzzy ART-GL with application to the recognition problems.