DSNNs:learning transfer from deep neural networks to spiking neural networks

• 作 者: 张磊 Du Zidong Li Ling Chen Yunj
• 机 构: StateKeyLaboratoryofComputerArchitecture,InstituteofComputingTechnology,CambriconTech.Ltd,Instituteo
• 出 处: 高技术通讯:英文版
• 发表日期: 2020年2期
• 关键词: DEEP leaning SPIKING NEURAL network(SNN) CONVERT METHOD spatially folded NETWORK
• 基金项目: the National Natural Science Foundation of China(No.61732007),Strategic Priority Research Program of Chinese Academy of Sciences(XDB32050200,XDC01020000).

Deep neural networks(DNNs)have drawn great attention as they perform the state-of-the-art results on many tasks.Compared to DNNs,spiking neural networks(SNNs),which are considered as the new generation of neural networks,fail to achieve comparable perform