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Conferences > CLEO_Europe > 1998 > CWF > CWF73

Optical Neural Network Training on a Reconfigurable Processor

T. J. Naughton, J. G. Keating, J. Rott, and M. Klíma

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Abstract

We present the initial experiments of a project to train large-scale artificial neural networks (ANNs) using a reconfigurable optical processing system. The system is built around a Calomel (mercurous chloride) acousto-optic (AO) matrix-vector multiplier[1]. The matrix of weights are displayed on a two-dimensional LCD (liquid crystal display) panel and the input vector is encoded in the acoustic wave of the AO unit. This system has been investigated in order to determine the processing limits due to (i) the combination of individual components and to (ii) the fundamental limits imposed by the nature of this optical processing technique.

© 1998 IEEE

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