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Proceedings Paper

Optical winner-take-all neural network using electron trapping materials
Author(s): Xiangyang Yang; William M. Seiderman; Ravindra A. Athale; Michael Astor
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Paper Abstract

Exemplar-based neural net classifiers enjoy extremely rapid learning procedures and are particularly suitable for analog optical hardware implementations. The winner-take-all (WTA) network is a key component in exemplar-based neural net classifiers as well as in optical competitive learning architectures. In this paper, we present an optical WTA network based on novel electron trapping (ET) materials. The mathematical model has been modified for the optical implementation. All the neuron operations required by the WTA network such as self- excitation, lateral inhibition and thresholding, are performed by a single ET device.

Paper Details

Date Published: 1 July 1992
PDF: 12 pages
Proc. SPIE 1701, Optical Pattern Recognition III, (1 July 1992); doi: 10.1117/12.138338
Show Author Affiliations
Xiangyang Yang, Quantex Corp. (United States)
William M. Seiderman, Quantex Corp. (United States)
Ravindra A. Athale, George Mason Univ. (United States)
Michael Astor, George Mason Univ. (United States)

Published in SPIE Proceedings Vol. 1701:
Optical Pattern Recognition III
David P. Casasent; Tien-Hsin Chao, Editor(s)

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