A survey of adaptive resonance theory neural network models for engineering applications
This survey samples from the ever-growing family of adaptive resonance theory (ART)
neural network models used to perform the three primary machine learning modalities,
namely, unsupervised, supervised and reinforcement learning. It comprises a representative
list from classic to contemporary ART models, thereby painting a general picture of the
architectures developed by researchers over the past 30 years. The learning dynamics of
these ART models are briefly described, and their distinctive characteristics such as code …
neural network models used to perform the three primary machine learning modalities,
namely, unsupervised, supervised and reinforcement learning. It comprises a representative
list from classic to contemporary ART models, thereby painting a general picture of the
architectures developed by researchers over the past 30 years. The learning dynamics of
these ART models are briefly described, and their distinctive characteristics such as code …
A Survey of Adaptive Resonance Theory Neural Network Models for Engineering Applications
L Enzo Brito da Silva, I Elnabarawy… - arXiv e …, 2019 - ui.adsabs.harvard.edu
This survey samples from the ever-growing family of adaptive resonance theory (ART)
neural network models used to perform the three primary machine learning modalities,
namely, unsupervised, supervised and reinforcement learning. It comprises a representative
list from classic to modern ART models, thereby painting a general picture of the
architectures developed by researchers over the past 30 years. The learning dynamics of
these ART models are briefly described, and their distinctive characteristics such as code …
neural network models used to perform the three primary machine learning modalities,
namely, unsupervised, supervised and reinforcement learning. It comprises a representative
list from classic to modern ART models, thereby painting a general picture of the
architectures developed by researchers over the past 30 years. The learning dynamics of
these ART models are briefly described, and their distinctive characteristics such as code …
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