Optoelectronic implementations of neural networks

The ability of optical systems to provide the massive interconnections between processors required in most neural network models, which constitutes their chief advantage for such applications, is discussed, focusing on holography. Because of the essential nonlinearity of the holographic connections, nonlinear processing elements are needed to perform complex computations. The use of GaAs hybrid optoelectronic processing elements is examined. GaAs is an excellent material for this purpose, since it can be used to fabricate both fast electronic circuits and optical sources and detectors. It is shown how a complete hybrid neural computer can be implemented using available technology developed for conventional computing. An experimentally demonstrated network in which optics plays an even larger role is described.<>