中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 自动化研究所
  3. 中国科学院自动化研究所
  4. 脑图谱与类脑智能实验室
  5. 类脑认知计算
GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity

文献类型：期刊论文

作者Zhao, Dongcheng1,4; Zeng, Yi1,2,3,4; Zhang, Tielin1; Shi, Mengting1,4; Zhao, Feifei1
刊名FRONTIERS IN COMPUTATIONAL NEUROSCIENCE
出版日期2020-11-12
卷号14页码:12
关键词SNN plasticity brain local STDP global feedback alignment
DOI10.3389/fncom.2020.576841
通讯作者Zeng, Yi(yi.zeng@ia.ac.cn)
英文摘要Spiking Neural Networks (SNNs) are considered as the third generation of artificial neural networks, which are more closely with information processing in biological brains. However, it is still a challenge for how to train the non-differential SNN efficiently and robustly with the form of spikes. Here we give an alternative method to train SNNs by biologically-plausible structural and functional inspirations from the brain. Firstly, inspired by the significant top-down structural connections, a global random feedback alignment is designed to help the SNN propagate the error target from the output layer directly to the previous few layers. Then inspired by the local plasticity of the biological system in which the synapses are more tuned by the neighborhood neurons, a differential STDP is used to optimize local plasticity. Extensive experimental results on the benchmark MNIST (98.62%) and Fashion MNIST (89.05%) have shown that the proposed algorithm performs favorably against several state-of-the-art SNNs trained with backpropagation.
WOS关键词DYNAMICAL SYNAPSES ; NEURONS ; MODELS
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDB32070100] ; Ministry of Science and Technology of the People's Republic of China[2020AAA0104305] ; Beijing Municipal Commission of Science and Technology[Z181100001518006] ; CETC Joint Fund[6141B08010103] ; Beijing Academy of Artificial Intelligence (BAAI)
WOS研究方向Mathematical & Computational Biology ; Neurosciences & Neurology
语种英语
WOS记录号WOS:000592195800001
出版者FRONTIERS MEDIA SA
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; Ministry of Science and Technology of the People's Republic of China ; Beijing Municipal Commission of Science and Technology ; CETC Joint Fund ; Beijing Academy of Artificial Intelligence (BAAI)
源URL[http://ir.ia.ac.cn/handle/173211/41774]  
专题类脑智能研究中心_类脑认知计算
通讯作者Zeng, Yi
作者单位1.Chinese Acad Sci, Inst Automat, Res Ctr Brain Inspired Intelligence, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing, Peoples R China
3.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Beijing, Peoples R China
4.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Zhao, Dongcheng,Zeng, Yi,Zhang, Tielin,et al. GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity[J]. FRONTIERS IN COMPUTATIONAL NEUROSCIENCE,2020,14:12.
APA Zhao, Dongcheng,Zeng, Yi,Zhang, Tielin,Shi, Mengting,&Zhao, Feifei.(2020).GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity.FRONTIERS IN COMPUTATIONAL NEUROSCIENCE,14,12.
MLA Zhao, Dongcheng,et al."GLSNN: A Multi-Layer Spiking Neural Network Based on Global Feedback Alignment and Local STDP Plasticity".FRONTIERS IN COMPUTATIONAL NEUROSCIENCE 14(2020):12.

入库方式： OAI收割

来源：自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。