scholarly journals Adaptive resonance theory based neural networks ? the ?ART? of real-time pattern recognition in chemical process monitoring?

1995 ◽  
Vol 14 (8) ◽  
pp. 398-406 ◽  
Author(s):  
D WIENKE ◽  
L BUYDENS
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Real Time ◽  
Process Monitoring ◽  
Chemical Process ◽  
Adaptive Resonance Theory ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Time Pattern ◽  
Chemical Process Monitoring

scholarly journals Neural Networks Art: Solving Problems with Multiple Solutions and New Teaching Algorithm

2014 ◽  
Vol 8 (1) ◽  
pp. 15-21
Author(s):  
Dmitrienko V. D ◽  
Yu. Zakovorotnyi A ◽  
Yu. Leonov S ◽  
Khavina I. P
Keyword(s):  
Neural Networks ◽  
Multiple Solutions ◽  
Input Data ◽  
Learning Algorithms ◽  
Adaptive Resonance Theory ◽  
Classification Methods ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Noisy Input ◽  
New Algorithms

A new discrete neural networks adaptive resonance theory (ART), which allows solving problems with multiple solutions, is developed. New algorithms neural networks teaching ART to prevent degradation and reproduction classes at training noisy input data is developed. Proposed learning algorithms discrete ART networks, allowing obtaining different classification methods of input.

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