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Proceedings Paper

Optical laboratory realization of a symbolic production system
Author(s): David P. Casasent; Elizabeth C. Botha; Jin-Yun Wang; Ren-Chao Ye
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Paper Abstract

An optical symbolic neural net is described. It uses an optical symbolic correlator. This produces a new input neuron representation space that is shift-invariant and can accommodate multiple objects. No other neural net can handle multiple objects within the field of view. Initial optical laboratory data are presented. An optical neural net production system processes this new neuron data. This aspect of the system is briefly described.

Paper Details

Date Published: 1 September 1990
PDF: 12 pages
Proc. SPIE 1295, Real-Time Image Processing II, (1 September 1990); doi: 10.1117/12.21238
Show Author Affiliations
David P. Casasent, Carnegie Mellon Univ. (United States)
Elizabeth C. Botha, Carnegie Mellon Univ. (United States)
Jin-Yun Wang, Carnegie Mellon Univ. (United States)
Ren-Chao Ye, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 1295:
Real-Time Image Processing II
Richard D. Juday, Editor(s)

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