AN ALL-OPTICAL HOPFIELD NETWORK: THEORY AND EXPERIMENT

The implementation of an all-optical Hopfield-type neural network is made possible by eliminating the need for subtracting light intensities. This implementation is achieved without significantly degrading the network's performance, when only inhibitory connections (i.e., Jij <0) are used. The theoretical analysis of such a network, and its experimental implementation, exploiting a liquid crystal light valve for the neurons and an array of subholograms for the interconnections, are presented.