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Proceedings Paper

Mixed analog/digital VLSI design and simulation of an adaptive resonance theory (ART) neural network architecture
Author(s): Juin J. Liou; Ching S. Ho; Christos G. Christodoulou; L. Chan
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Paper Abstract

This paper presents a mixed analog/digital circuit design for an adaptive resonance theory (ART) architecture, called the augmented adaptive resonance theory-I neural network (AART1-NN). The circuit is implemented based on the transconductance-mode approach and mixed analog/digital components, in which analog circuits are used to fully incorporate the parallel mechanism of the neural network, whereas digital circuits are used to provide a reduced circuit size as well as more precise multiplication operation. It is shown that the Pspice simulation results of the implemented circuit are in good agreement with the results calculated numerically from the coupled nonlinear differential equations governing the AART1-NN.

Paper Details

Date Published: 6 April 1995
PDF: 12 pages
Proc. SPIE 2492, Applications and Science of Artificial Neural Networks, (6 April 1995); doi: 10.1117/12.205197
Show Author Affiliations
Juin J. Liou, Univ. of Central Florida (United States)
Ching S. Ho, Univ. of Central Florida (United States)
Christos G. Christodoulou, Univ. of Central Florida (United States)
L. Chan, Air Force Wright Lab. (United States)


Published in SPIE Proceedings Vol. 2492:
Applications and Science of Artificial Neural Networks
Steven K. Rogers; Dennis W. Ruck, Editor(s)

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