Abstract

A space–time-sharing optical neural network for implementing a large-scale operation is presented. If the interconnection weight matrix is partitioned into an array of submatrices, a large space–bandwidth pattern can be processed with a smaller neural network. We show that the processing time increases as a square function of the space–bandwidth product of the pattern. To illustrate the space–time-sharing operation, experimental and simulated results are provided.

© 1991 Optical Society of America

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