Optoelectronic implementations of neural networks
Optoelectronic implementations of neural networks
复制标题
神经网络的光电实现
DOI：
10.1109/35.41399
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发表时间：
1989
影响因子：
11.2
通讯作者：
D. Brady
中科院分区：
文献类型：
--
作者：
D. Psaltis;A. Yamamura;K. Hsu;Steven Lin;Xiang;D. Brady
讨论了光学系统在大多数神经网络模型所需的处理器之间提供大规模互连的能力，这构成了光学系统在此类应用中的主要优势，重点是全息术。由于全息连接本质上是非线性的，因此需要非线性处理元件来执行复杂的计算。研究了砷化镓混合光电处理元件的使用。 GaAs 是用于此目的的优异材料，因为它可用于制造快速电子电路以及光源和探测器。它展示了如何使用为传统计算开发的可用技术来实现完整的混合神经计算机。描述了一个经过实验证明的网络，其中光学发挥着更大的作用。<<ETX>>
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.<<ETX>>