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Proceedings Paper

Unipolar terminal-attractor-based neural associative memory with adaptive threshold and perfect convergence
Author(s): Chwan-Hwa Wu; Hua-Kuang Liu
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Paper Abstract

Recently, a terminal attractor based associative memory (TABAM) with optical implementation techniques was published in Applied Optics (August 10, 1992). Herein perfect convergence and correct retrieval of the TABAM are demonstrated via computer simulation by adaptively setting the threshold values for the dynamic iteration for the unipolar binary neuron states using terminal-attractors and an inner-product approach. The simulations are completed by (1) exhaustive tests with all of the possible combinations of stored and test vectors in small- scale networks, and (2) Monte Carlo simulations with randomly generated stored and test vectors in large scale networks with a M/N ratio equals 4 (M: the number of stored vectors; and N: the number of neurons up to 256). The feasibility of optoelectronic implementation is discussed.

Paper Details

Date Published: 7 December 1994
PDF: 11 pages
Proc. SPIE 2430, Optical Memory & Neural Networks '94: Optical Neural Networks, (7 December 1994); doi: 10.1117/12.195622
Show Author Affiliations
Chwan-Hwa Wu, Auburn Univ. (United States)
Hua-Kuang Liu, Jet Propulsion Lab. (United States)

Published in SPIE Proceedings Vol. 2430:
Optical Memory & Neural Networks '94: Optical Neural Networks
Andrei L. Mikaelian, Editor(s)

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