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Proceedings Paper

Optical Neural Classification Of Binary Patterns
Author(s): Steven C Gustafson; Gordon R Little
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Paper Abstract

Binary pattern classification that may be implemented using optical hardware and neural network algorithms is considered. Pattern classification problems that have no concise description (as in classifying handwritten characters) or no concise computation (as in NP-complete problems) are expected to be particularly amenable to this approach. For example, optical processors that efficiently classify binary patterns in accordance with their Boolean function complexity might be designed. As a candidate for such a design, an optical neural network model is discussed that is designed for binary pattern classification and that consists of an optical resonator with a dynamic multiplex-recorded reflection hologram and a phase conjugate mirror with thresholding and gain. In this model, learning or training examples of binary patterns may be recorded on the hologram such that one bit in each pattern marks the pattern class. Any input pattern, including one with an unknown class or marker bit, will be modified by a large number of parallel interactions with the reflection hologram and nonlinear mirror. After perhaps several seconds and 100 billion interactions, a steady-state pattern may develop with a marker bit that represents a minimum-Boolean-complexity classification of the input pattern. Computer simulations are presented that illustrate progress in understanding the behavior of this model and in developing a processor design that could have commanding and enduring performance advantages compared to current pattern classification techniques.

Paper Details

Date Published: 3 May 1988
PDF: 7 pages
Proc. SPIE 0882, Neural Network Models for Optical Computing, (3 May 1988); doi: 10.1117/12.944104
Show Author Affiliations
Steven C Gustafson, University of Dayton Research Institute (United States)
Gordon R Little, University of Dayton Research Institute (United States)


Published in SPIE Proceedings Vol. 0882:
Neural Network Models for Optical Computing
Ravindra A. Athale; Joel Davis, Editor(s)

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