Title
Hardware implementation of ART1 memories using a mixed analog/digital approach
Abstract
This paper presents a VLSI circuit implementation for both the short-term memory (STM) and long-term memory (LTM) of the adaptive resonance theory neural network (ART1-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 provide a reduced circuit size as well as a more precise multiplication operation. A simple analog-to-digital (A/D) converter is also included to realize binary STM activities and characterize the quenching threshold. The PSpice simulation results of the implemented circuits are in good agreement with the exact solutions of the coupled nonlinear differential equations.
Publication Date
12-1-1994
Publication Title
IEEE International Conference on Neural Networks - Conference Proceedings
Volume
4
Number of Pages
2137-2142
Document Type
Article; Proceedings Paper
Identifier
scopus
Personal Identifier
scopus
Copyright Status
Unknown
Socpus ID
0028734147 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0028734147
STARS Citation
Ho, C. S.; Liou, J. J.; and Georgiopoulos, M., "Hardware implementation of ART1 memories using a mixed analog/digital approach" (1994). Scopus Export 1990s. 49.
https://stars.library.ucf.edu/scopus1990/49