scholarly journals Unsupervised adaptive resonance theory neural networks for control chart pattern recognition

2001 ◽  
Vol 215 (1) ◽  
pp. 59-67 ◽  
Author(s):  
D T Pham ◽  
A B Chan
Keyword(s):  
Neural Networks ◽  
Pattern Recognition ◽  
Control Chart ◽  
Adaptive Resonance Theory ◽  
Resonance Theory ◽  
Adaptive Resonance ◽  
Control Chart Pattern

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.

Sign in / Sign up

Export Citation Format

Share Document