Hardware implementation of an adaptive resonance theory (ART) neural network using compensated operational amplifiers

Ching S. Ho; Juin J. Liou; Michael Georgiopoulos; Christos G. Christodoulou

doi:10.1117/12.169983

2 March 1994 Hardware implementation of an adaptive resonance theory (ART) neural network using compensated operational amplifiers

Ching S. Ho, Juin J. Liou, Michael Georgiopoulos, Christos G. Christodoulou

Author Affiliations +

Proceedings Volume 2243, Applications of Artificial Neural Networks V; (1994) https://doi.org/10.1117/12.169983
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

This paper presents an analog circuit design and implementation for an adaptive resonance theory neural network architecture called the augmented ART1 neural network (AART1-NN). Practical monolithic operational amplifiers (Op-Amps) LM741 and LM318 are selected to implement the circuit, and a simple compensation scheme is developed to adjust the Op-Amp electrical characteristics to meet the design requirement. A 7-node prototype circuit has been designed and verified using the Pspice circuit simulator run on a Sun workstation. Results simulated from the AART1-NN circuit using the LM741, LM318, and ideal Op-Amps are presented and compared.

Citation Download Citation

Ching S. Ho, Juin J. Liou, Michael Georgiopoulos, and Christos G. Christodoulou "Hardware implementation of an adaptive resonance theory (ART) neural network using compensated operational amplifiers", Proc. SPIE 2243, Applications of Artificial Neural Networks V, (2 March 1994); https://doi.org/10.1117/12.169983

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