Optical Implementations of Neural Computing

R. Athale
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Abstract

Achieving performance comparable to human beings in speech recognition, visual perception, motor control and knowledge acquisition, representation, and processing is one of the most difficult and exciting challenges facing the information processing research community. Recently neural net models of computation have been investigated as a novel approach for solving these problems. These proposed models are only loosely based on the known and postulated characteristics of biological systems and no claim is usually made for these models to be biologically accurate.
神经计算的光学实现
在语音识别、视觉感知、运动控制和知识获取、表示和处理方面取得与人类相当的性能是信息处理研究界面临的最困难和最激动人心的挑战之一。近年来,神经网络计算模型作为解决这些问题的一种新方法得到了研究。这些提出的模型只是松散地基于已知的和假定的生物系统的特征,通常没有要求这些模型在生物学上是准确的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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