电工技术学报2020，Vol.35Issue(2)：225-235,11.DOI:10.19595/j.cnki.1000-6753.tces.181701
基于突触可塑性的自适应脉冲神经网络在高斯白噪声刺激下的抗扰功能研究
Research on Disturbance Rejection of Adaptive Spiking Neural Network Based on Synaptic Plasticity under White Gaussian Noise
摘要
Abstract
With the electromagnetic environment becoming more and more complex, theshortcomings of traditional anti-electromagnetic disturbance methods are becoming increasingly prominent. The organism under the regulation of nervous system has the advantages on self-organization, self-adaption and disturbance rejection. It is significant to explore a new method of anti-electromagnetic disturbance based on the excellent characteristics of organism. Therefore, a new field of electromagnetic bionic protection emerged. In this paper, the disturbance rejection of the spiking neural network based on excitatory synaptic plasticity and inhibitory synaptic plasticity was analyzed. A ten-layer feed-forward spiking neural network was constructed. The firing rate and correlation between membrane potential of the neuron were considered as indexes for assessing disturbance rejection ability. The experimental results show that: under a certain intensity of white Gaussian noise disturbance, the relative variation of output firing rate is tiny; the correlation between membrane potential in output layer is relatively large. It is concluded that the spiking neural network based on synaptic plasticity has a certain ability to reject noise disturbance. This study lays the theoretical foundation for improving the protection ability of electronic system in the complex electromagnetic environment.关键词
脉冲神经网络/突触可塑性/抗扰/高斯白噪声Key words
Spiking neural network/synaptic plasticity/disturbance rejection/white Gaussian noise分类
生物科学引用本文复制引用
郭磊,刘东钊,黄凤荣,于洪丽..基于突触可塑性的自适应脉冲神经网络在高斯白噪声刺激下的抗扰功能研究[J].电工技术学报,2020,35(2):225-235,11.基金项目
This work is supported by the National Natural Science Foundation of China (61571180,51877068). （61571180,51877068）
