Name
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 tales 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. |
Year | DOI | Venue |
|---|---|---|
1997 | 10.1109/ICNN.1997.614203 | 1997 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS, VOLS 1-4 |
Keywords | Field | DocType |
adaptive control,adaptive resonance theory,adaptive filters,resonance,recall,category theory,information processing,unsupervised learning,neural networks,choice function,fuzzy control,business | Adaptive resonance theory,Categorization,Neuro-fuzzy,Computer science,Fuzzy logic,Vigilance (psychology),Unsupervised learning,Artificial intelligence,Adaptive neuro fuzzy inference system,Machine learning,Choice function | Conference |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| pierre lavoie | 1 | 0 | 0.34 |
| Jean-Francois Crespo | 2 | 18 | 1.74 |
| Yvon Savaria | 3 | 566 | 139.13 |