光学非线性激活函数器件的原理与应用  

Principles and Applications for Optical Nonlinear Activation Function Devices

作　　者：吕青鸿 马睿 肖莘宇 俞维嘉 刘知非 胡小永[1,4] 龚旗煌 LüQinghong;Ma Rui;Xiao Shenyu;Yu Weijia;Liu Zhifei;Hu Xiaoyong;Gong Qihuang(State Key Laboratory of Artificial Microstructure and Mesoscopic Physics,School of Physics,Peking University,Beijing 100871,China;School of Physics,Nankai University,Tianjin 300071,China;Institute of Information Photonics Technology,Faculty of Science,Beijing University of Technology,Beijing 100124,China;Collaborative Innovation Center of Extreme Optics,Shanxi University,Taiyuan 030006,Shanxi,China)

机构地区：[1]北京大学物理学院人工微结构和介观物理国家重点实验室,北京100871 [2]南开大学物理科学学院,天津300071 [3]北京工业大学理学部信息光子技术研究所,北京100124 [4]山西大学极端光学协同创新中心,山西太原030006

出　　处：《光学学报》2023年第16期1-19,共19页Acta Optica Sinica

摘　　要：神经网络中的非线性激活层可以改变多层网络数据间的线性变换关系,使神经网络得以进行更复杂的学习。为实现处理速度更快,能耗更低的运算,近年来光子领域的神经网络逐渐受到重视,一系列光学非线性激活函数器件应运而生。本文综述了近年来在光学神经网络中引入非线性激活函数的工作,从光学非线性函数的物理机制及其在光学神经网络中的应用出发,对该领域的工作进行了回顾;总结并讨论了光学神经网络中光学非线性激活函数器件发展所面临的挑战及变化趋势,并基于此展望了其发展前景。Significance In recent years,with the development of computer technology,artificial intelligence has gradually penetrated many aspects of current human life.As the basic architecture of artificial intelligence,machine learning and neural networks have been given increasingly more attention to by researchers in recent years.At present,neural networks have been applied in matrix calculation,equation solving,data analysis,and many other fields,and have become a research field with great development potential in the 21st century.In conventional neural networks,linear functions are the primary mathematical tool.Nowadays,nonlinear activation functions(NAFs)can be employed to describe a large number of different systems,such as electric power systems,optical systems,economic systems,biological systems,computer networks,and communication systems.Nonlinear functions are a much more powerful mathematical tool than linear functions.Therefore,they are introduced into the neural networks to apply the neural networks to more nonlinear models.Currently,the application of nonlinear functions in neural networks is mainly realized through the nonlinear activation layers.The nonlinear activation layers of neural networks(NNs)can alter the linear transformation relationship beteween multi-layer networks,and thus enabling the NNs to solve more complex and advanced learning with flexibility.In pursuit of faster processing speed and lower energy consumption,optical neural networks(ONNs)have caught much attention from researchers in recent years.The response time of photons in ONNs is often picoseconds,and the energy loss of optical systems is often lower than that of electronic systems.Thus,the design of ONNs features high throughput and low power consumption.Therefore,except for electronic systems,photonic systems have shown a broad development prospect in computing.Additionally,the intelligent photonics represented by ONNs has also emerged and become an important development direction of information processing in the future.As an ind

关 键 词：非线性光学 光学神经网络 非线性激活函数 

分 类 号：O436[机械工程—光学工程]