Abstract

The massive interconnection and parallel operation in an optical neural network (ONN) require a high-resolution, large-dynamic-range spatial light modulator (SLM) for the construction of the interconnectionweight matrix (IWM). However, the resolution of currently available SLM's is limited, and this is a major obstacle in the development of a large-scale optical neural computers. We use a space-time-sharing technique to improve the resolution of an optical neural operation. Because the ONN we recently developed¹ uses incoherent light, the space–bandwidth product of the network can be expanded by space-time multiplexing. In other words, a large-scale neural operation can be accomplished with a smaller network, by trading off the processing speed. To accomplish this task, we have shown that a large-scale IWM can be partitioned into arrays of sub-IWM's, of which the space–bandwidth product of the sub-IWM's is equal to the number of neurons in the neural network. Then by sequentially displaying these arrays of sub-IWM's, a larger (nfold) space–bandwidth image pattern can be obtained by using a smaller ONN. Computer-simulated results and experimental demonstrations are also provided in this paper.

© 1990 Optical Society of America