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Adaptive resonance theory

Known as: ART 
Adaptive resonance theory (ART) is a theory developed by Stephen Grossberg and Gail Carpenter on aspects of how the brain processes information. It… 
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Related topics

Related topics

7 relations
Algebraic equationArtificial neural networkEncog Machine Learning FrameworkMemory-prediction framework

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2015
Highly Cited
2015
Linear feature selection and classification using PNN and SFAM neural networks for a nearly online diagnosis of bearing naturally progressing degradations
Highly Cited
2010
Highly Cited
2010
The Fuzzy ART algorithm: A categorization method for supplier evaluation and selection
Highly Cited
2008
Highly Cited
2008
Extensions of vector quantization for incremental clustering
Highly Cited
2006
Highly Cited
2006
RT-UNNID: A practical solution to real-time network-based intrusion detection using unsupervised neural networks
Highly Cited
2004
Highly Cited
2004
Integration of ART-Kohonen neural network and case-based reasoning for intelligent fault diagnosis
1999
1999
Adaptive Resonance Theory Microchips
Recently, a real-time clustering microchip based on the ART1 algorithm has been reported. That chip was able to classify 100-bit… 
Highly Cited
1999
Highly Cited
1999
Fuzzy ARTMAP based electronic nose data analysis
Highly Cited
1995
Highly Cited
1995
A modified fuzzy ARTMAP architecture for the approximation of noisy mappings
Highly Cited
1991
Highly Cited
1991
Vector associative maps: Unsupervised real-time error-based learning and control of movement trajectories
Review
1989
Review
1989
Neural network models for pattern recognition and associative memory
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