使用光折变介质的感知器光学实现

John H. Hong, S. Campbell, P. Yeh
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引用次数: 1

摘要

虽然体全息图为许多信息处理任务提供了强大的互连手段,但实现神经网络学习算法所需的自适应互连能力在光折变晶体中几乎是理想的实现。动态全息图中光栅是实时建立的,不需要单独的开发周期,这使得它们对神经实现很有吸引力[1-3]。这一点,再加上体全息图固有的高密度信息存储能力(例如,在~1 cm3中有~1012个互连[4]),使得光折变实现在许多神经实现技术中是独一无二的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optical Implementation of Perceptrons Using Photorefractive Media
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.
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