DocumentCode
314407
Title
Multiple categorization using fuzzy ART
Author
Lavoie, Pierre ; Crespo, Jean-François ; Savaria, Yvon
Author_Institution
Defence Res. Establ., Ottawa, Ont., Canada
Volume
3
fYear
1997
fDate
9-12 Jun 1997
Firstpage
1983
Abstract
The internal competition between categories in the fuzzy adaptive resonance theory (ART) neural model can be biased by replacing the original choice function with one that contains a tuning parameter under external control. The competition can be biased, so that, for example, categories of a desired size can be favored. This attentional tuning mechanism allows recalling for a same input different categories under different circumstances, even when no additional learning tabes place. A new tuning parameter is unnecessary, since the readily available vigilance parameter can control both attentional tuning and vigilance. The modified fuzzy ART has the self-stabilization property for analog inputs, whether vigilance is fixed or variable
Keywords
ART neural nets; category theory; fuzzy neural nets; search problems; unsupervised learning; attentional tuning mechanism; fuzzy ART; fuzzy adaptive resonance theory neural model; internal competition; multiple categorization; recall; self-stabilization property; vigilance parameter; Adaptive control; Adaptive filters; Business; Fuzzy control; Humans; Information processing; Neural networks; Programmable control; Resonance; Subspace constraints;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.614203
Filename
614203
Link To Document