A survey of approaches for implementing optical neural networks

CASIA OpenIR

	A survey of approaches for implementing optical neural networks
	Runqin Xu
出版者	ELSEVIER SCI LTD
	2021
简介	Conventional neural networks are software simulations of artificial neural networks (ANNs) implemented on von Neumann machines. This technology has recently encountered bottlenecks in terms of computing speed and energy consumption, leading to increased research interest in optical neural networks (ONNs), which are expected to become the basis for the next generation of artificial intelligence. To provide a better understanding of ONNs and to motivate further developments in this field, previous studies of ONN are reviewed in this article. Our work mainly focuses on the mathematical operations that are decomposed from theoretical models of ANNs and their corresponding optical implementations; these include matrix multiplication, nonlinear activation, convolution, and learning algorithms realized via optical approaches. Some fundamental information about ANNs is also introduced to make this work friendlier to non-experts.
关键词	Artificial intelligence Optics Optical neural network
学科门类	工学 ; 工学::光学工程
URL	查看原文
收录类别	SCI
语种	英语
文献类型	期刊
条目标识符	http://ir.ia.ac.cn/handle/173211/57298
专题	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Runqin Xu.A survey of approaches for implementing optical neural networks:ELSEVIER SCI LTD,2021.