Synaptic delay plasticity based on frequency-switched VCSELs for optical delay-weight spiking neural networks

被引:0
|
作者
Lu, Yao [1 ]
Zhang, Wenjia [1 ,2 ]
Fu, Bangqi [1 ]
DU, Jiangbing [1 ,2 ]
He, Zuyuan [1 ,2 ]
机构
[1] Shanghai Jiao Tong Univ, State Key Lab Adv Opt Commun Syst & Networks, Shanghai 200240, Peoples R China
[2] Peng Cheng Lab, Shenzhen 518055, Peoples R China
基金
中国国家自然科学基金;
关键词
INTELLIGENCE;
D O I
10.1364/OL.470512
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
In this Letter, we propose an optical delay-weight spiking neural network (SNN) architecture constructed by cascaded frequency and intensity-switched vertical-cavity surface emitting lasers (VCSELs). The synaptic delay plasticity of frequency-switched VCSELs is deeply studied by numeri-cal analysis and simulations. The principal factors related to the delay manipulation are investigated with the tunable spiking delay up to 60 ns. Moreover, a two-layer spiking neu-ral network based on the delay-weight supervised learning algorithm is applied to a spiking sequence pattern training task and then a classification task of the Iris dataset. The proposed optical SNN provides a compact and cost-efficient solution for delay weighted computing architecture without considerations of extra programmable optical delay lines. (c) 2022 Optica Publishing Group
引用
收藏
页码:5587 / 5590
页数:4
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