A Plasticity-centric Approach to Train the Non-differential Spiking Neural Networks

	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	脑图谱与类脑智能实验室_神经计算与脑机交互
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
第一作者单位	中国科学院自动化研究所
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