Title
Hardware Implementation of An Adaptive Resonance Theory (ART) Neural Network Using Compensated Operational Amplifiers
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) LM74 1 and LM3 1 8 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.
Publication Date
3-2-1994
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Volume
2243
Number of Pages
344-355
Document Type
Article; Proceedings Paper
Identifier
scopus
Personal Identifier
scopus
DOI Link
https://doi.org/10.1117/12.169983
Copyright Status
Unknown
Socpus ID
1542801363 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/1542801363
STARS Citation
Ho, Ching S.; Liou, J. J.; and Georgiopoulos, M., "Hardware Implementation of An Adaptive Resonance Theory (ART) Neural Network Using Compensated Operational Amplifiers" (1994). Scopus Export 1990s. 170.
https://stars.library.ucf.edu/scopus1990/170