Articles listed below give examples of ART-based systems being used outside the CNS department at Boston University.
| Categories |
Topics:
Machine Learning,
Applications:
Industrial Control,
Models:
ART 2 / Fuzzy ART, |
| Author(s) |
Akimoto, Y. |
Izui, Y. |
Ogi, H. |
Tanaka, H. |
|
| Abstract |
The paper presents an artificial neural network (ANN) approach using ART2 (Adaptive Resonance Theory 2) to a diagnostic system for gas insulated switchgear (GIS). To begin with, the authors show the background of abnormality ... |
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| Categories |
Topics:
Image Analysis,
Applications:
Character Recognition,
Models:
ART 1, |
| Author(s) |
Capps, D. |
Caudell, T.P. |
Marks, R.J. |
Wunsch, D.C. |
|
| Abstract |
A solution to the problem of implementation of the adaptive resonance theory (ART) of neural networks that uses an optical correlator which allows the large body of correlator research to be leveraged in the implementation ... |
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| Categories |
Topics:
Image Analysis,
Applications:
Character Recognition,
Models:
ART 2-A, |
| Author(s) |
Kane, J.S. |
Paquin, M.J. |
|
| Abstract |
Adaptive resonance architectures are neural nets that are capable of classifying arbitrary input patterns into stable category representations. A hybrid optoelectronic implementation utilizing an optical joint transform ... |
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| Categories |
Topics:
Neural Hardware,
Applications:
Other,
Models:
ART 1, |
| Author(s) |
Caudell, T.P. |
|
| Abstract |
For industrial use, adaptive resonance theory (ART) neural networks have the potential of becoming an important component in a variety of commercial and military systems. Efficient software emulations of these networks are ... |
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| Categories |
Topics:
Image Analysis,
Applications:
Character Recognition,
|
| Author(s) |
Darling, R.B. |
Nabet, B. |
Pinter, R.B. |
|
| Abstract |
A neural network for processing sensory information. The network comprise one or more layers including interconnecting cells having individual states. Each cell is connected to one or more neighboring cells. Sensory signals ... |
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