Accession Number : ADP008620
Title : Custom Designed Electro-Optic Components for Optically Implemented, Multi-layer Neural Networks,
Corporate Author : COLORADO UNIV AT BOULDER DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
Personal Author(s) : Robinson, M. G. ; Johnson, K. M. ; Jared, D. ; Doroski, D. ; Wichart, S.
Report Date : 22 MAY 1992
Pagination or Media Count : 4
Abstract : Optical implementations of one-layer, perceptron-like neural networks have been shown to be very successful at associating pattern/target sets despite large system errors. It has shown that large systems can be realized with such architectures (> or = 40,000 interconnections), and appreciable processing speeds have been demonstrated (> 10 to the 8th power interconnections/sec). However, single layer networks are limited due to their inability to associate patterns that are not linearly separable. A more general network is the two-layer network, which is able to model arbitrary functions, and creat any decision boundary within the input vector pattern space. In order to implement such a network, it is necessary to perform a nonlinearity at the hidden layer before performing a subsequent matrix multiplication. In general, optical materials performing fast nonlinear processing require high optical powers. Hybrid opto-electronic devices can perform nonlinear operations at moderate speeds and low optical powers.
Descriptors : *ELECTROOPTICS, *NEURAL NETS, *LIGHT MODULATORS, *OPTICAL DETECTORS, PATTERN RECOGNITION, TARGET RECOGNITION, OPTICAL PROCESSING, CIRCUIT INTERCONNECTIONS, BEAM SPLITTING, OPTICAL LENSES, OPTICAL CIRCUITS, LIQUID CRYSTALS.
Subject Categories : Optical Detection and Detectors
Electrooptical and Optoelectronic Devices
Distribution Statement : APPROVED FOR PUBLIC RELEASE