| A review:Photonics devices,architectures,and algorithms for optical neural computing |
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| 作者姓名： | Shuiying Xiang Yanan Han Ziwei Song Xingxing Guo Yahui Zhang Zhenxing Ren Suhong Wang Yuanting Ma Weiwen Zou Bowen Ma Shaofu Xu Jianji Dong Hailong Zhou Quansheng Ren Tao Deng Yan Liu Genquan Han Yue Hao |
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| 作者单位： | State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology,School of Microelectronics,Xidian University,Xi'an 710071,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi'an 710071,China;State Key Laboratory of Advanced Optical Communication Systems and Networks,Intelligent Microwave Lightwave Integration Innovation Center(iMLic),Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;State Key Laboratory of Advanced Optical Communication Systems and Networks,Intelligent Microwave Lightwave Integration Innovation Center(iMLic),Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;State Key Laboratory of Advanced Optical Communication Systems and Networks,Intelligent Microwave Lightwave Integration Innovation Center(iMLic),Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;Wuhan National Laboratory for Optoelectronics,School of Optical and Electronic Information,Huazhong University of Science and Technology,Wuhan 430074,China;Wuhan National Laboratory for Optoelectronics,School of Optical and Electronic Information,Huazhong University of Science and Technology,Wuhan 430074,China;School of Electronics Engineering and Computer Science,Peking University,Beijing 100871,China;School of Physical Science and Technology,Southwest University,Chongqing 400715,China;State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology,School of Microelectronics,Xidian University,Xi'an 710071,China;State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology,School of Microelectronics,Xidian University,Xi'an 710071,China;State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology,School of Microelectronics,Xidian University,Xi'an 710071,China |
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| 基金项目： | This work was supported in part by the National Outstand-ing Youth Science Fund Project of National Natural Science Foundation of China;by the National Natural Sci-ence Foundation of China;by the Funda-mental Research Funds for the Central Universities |
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| 摘 要： | The explosive growth of data and information has motivated various emerging non-von Neumann computational approaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinating advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural computing in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives.
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| 关 键 词： | photonics neuron photonic STDP photonic spiking neural network optical reservoir computing optical convolutional neural network neuromorphic photonics |
A review:Photonics devices,architectures,and algorithms for optical neural computing |
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| Shuiying Xiang,Yanan Han,Ziwei Song,Xingxing Guo,Yahui Zhang,Zhenxing Ren,Suhong Wang,Yuanting Ma,Weiwen Zou,Bowen Ma,Shaofu Xu,Jianji Dong,Hailong Zhou,Quansheng Ren,Tao Deng,Yan Liu,Genquan Han,Yue Hao.A review:Photonics devices,architectures,and algorithms for optical neural computing[J].Chinese Journal of Semiconductors,2021,42(2):66-82. |
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| Authors: | Shuiying Xiang Yanan Han Ziwei Song Xingxing Guo Yahui Zhang Zhenxing Ren Suhong Wang Yuanting Ma Weiwen Zou Bowen Ma Shaofu Xu Jianji Dong Hailong Zhou Quansheng Ren Tao Deng Yan Liu Genquan Han Yue Hao |
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| Abstract: | The explosive growth of data and information has motivated various emerging non-von Neumann computational ap-proaches in the More-than-Moore era.Photonics neuromorphic computing has attracted lots of attention due to the fascinat-ing advantages such as high speed,wide bandwidth,and massive parallelism.Here,we offer a review on the optical neural com-puting in our research groups at the device and system levels.The photonics neuron and photonics synapse plasticity are presented.In addition,we introduce several optical neural computing architectures and algorithms including photonic spiking neural network,photonic convolutional neural network,photonic matrix computation,photonic reservoir computing,and photonic reinforcement learning.Finally,we summarize the major challenges faced by photonic neuromorphic computing,and propose promising solutions and perspectives. |
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| Keywords: | photonics neuron photonic STDP photonic spiking neural network optical reservoir computing optical convolution-al neural network neuromorphic photonics |
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