Abstract

While volume holograms offer a powerful means for providing interconnections for many information processing tasks, the adaptable interconnection capability necessary for implementing learning algorithms for neural networks finds an almost ideal realization in photorefractive crystals. The dynamic holograms in which gratings are built up in real time without the need for separate development cycles make them appealing for neural implementations [1-3]. This, coupled with the highly dense information storage capability that is inherent in volume holograms (e.g.,~10¹² interconnections in ~1 cm³ [4]) make photorefractive implementations unique among many neural implementation technologies.

© 1990 Optical Society of America