Fuzzy Adaptive Resonance Theory with Group Learning and its Applications
نویسندگان
چکیده
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 effective 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.
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