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Proceedings Paper

Improved adaptive resonance theory
Author(s): Frank Yeong-Chya Shih; Jenlong Moh
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Paper Abstract

Adaptive resonance theory (ART) has been used to develop neural network architectures in order to self-organize pattern recognition codes stably in real-time in response to random input sequences of patterns. A brief background of the motivations and design considerations underlying the development of adaptive resonance networks an outline of their basic operation a new idea for improving the model and some experimental results are discussed in this article. 1.

Paper Details

Date Published: 1 February 1991
PDF: 11 pages
Proc. SPIE 1382, Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods, (1 February 1991); doi: 10.1117/12.25195
Show Author Affiliations
Frank Yeong-Chya Shih, New Jersey Institute of Technology (United States)
Jenlong Moh, New Jersey Institute of Technology (United States)


Published in SPIE Proceedings Vol. 1382:
Intelligent Robots and Computer Vision IX: Neural, Biological, and 3D Methods
David P. Casasent, Editor(s)

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