CASIA OpenIR  > 类脑智能研究中心  > 神经计算及脑机交互
A Plasticity-centric Approach to Train the Non-differential Spiking Neural Networks
Zhang TL(张铁林)1,2; Ceng Y(曾毅)1,2,3; Zhao DC(赵东城)1,3; Shi MT(史梦婷)1,3; Tielin Zhang, Yi Zeng
2018-02
会议名称Thirty-Second AAAI Conference on Artificial Intelligence (AAAI 2018)
会议日期February 2-7, 2018
会议地点New Orleans, Louisiana, USA.
摘要Many efforts have been taken to train spiking neural networks (SNNs), but most of them still need improvements due to the discontinuous and non-differential characteristics of SNNs. While the mammalian brains solve these kinds of problems by integrating a series of biological plasticity learning rules. In this paper, we will focus on two biological plausible methodologies and try to solve these catastrophic training problems in SNNs. Firstly, the biological neural network will try to keep a balance between inputs and outputs on both the neuron and the network levels. Secondly, the biological synaptic weights will be passively updated by the changes of the membrane potentials of the neighbour-hood neurons, and the plasticity of synapses will not propagate back to other previous layers. With these biological inspirations, we propose Voltage-driven Plasticity-centric SNN (VPSNN), which includes four steps, namely: feed forward inference, unsupervised equilibrium state learning, supervised last layer learning and passively updating synaptic weights based on spiketiming dependent plasticity (STDP). Finally we get the accuracy of 98.52% on the hand-written digits classification task on MNIST. In addition, with the help of a visualization tool, we try to analyze the black box of SNN and get better understanding of what benefits have been acquired by the proposed method.
关键词Spiking Neural Network
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/22081
专题类脑智能研究中心_神经计算及脑机交互
通讯作者Tielin Zhang, Yi Zeng
作者单位1.Institute of Automation, Chinese Academy of Sciences, Beijing, China
2.Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
3.University of Chinese Academy of Sciences, Beijing, China
推荐引用方式
GB/T 7714
Zhang TL,Ceng Y,Zhao DC,et al. A Plasticity-centric Approach to Train the Non-differential Spiking Neural Networks[C],2018.
条目包含的文件 下载所有文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
final-round-AAAI2018(2572KB)会议论文 开放获取CC BY-NC-SA浏览 下载
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Zhang TL(张铁林)]的文章
[Ceng Y(曾毅)]的文章
[Zhao DC(赵东城)]的文章
百度学术
百度学术中相似的文章
[Zhang TL(张铁林)]的文章
[Ceng Y(曾毅)]的文章
[Zhao DC(赵东城)]的文章
必应学术
必应学术中相似的文章
[Zhang TL(张铁林)]的文章
[Ceng Y(曾毅)]的文章
[Zhao DC(赵东城)]的文章
相关权益政策
暂无数据
收藏/分享
文件名: final-round-AAAI2018-tielinzhang-11-20.pdf
格式: Adobe PDF
所有评论 (0)
暂无评论
 

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。