Title :
Fuzzy Adaptive Resonance Theory Combining Overlapped Category in consideration of connections
Author :
Isawa, Haruka ; Matsushita, Haruna ; Nishio, Yoshifumi
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokushima Univ., Tokushima
Abstract :
Adaptive resonance theory (ART) is an unsupervised neural network. Fuzzy ART (FART) is a variation of ART, allows both binary and continuous input patterns. However, fuzzy ART has the category proliferation problem. In this study, to solve this problem, we propose a new fuzzy ART algorithm: fuzzy ART combining overlapped category in consideration of connections (C-FART). C-FART has two important features. One is to make connections between similar categories. The other is to combine overlapping categories into with connections one category. We investigate the behavior of C-FART, and compare C-FART with the conventional FART.
Keywords :
adaptive resonance theory; fuzzy neural nets; fuzzy adaptive resonance theory; overlapped category; unsupervised neural network; Adaptive systems; Fuzzy logic; Humans; Neural networks; Neurons; Pattern recognition; Predictive models; Resonance; Subspace constraints; Supervised learning;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4634312
