Research on Disturbance Rejection of Adaptive Spiking Neural Network Based on Synaptic Plasticity under White Gaussian Noise
Guo Lei1,2, Liu Dongzhao1,2, Huang Fengrong3, Yu Hongli1,2
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300130 China; 2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin 300130 China; 3. School of Mechanical Engineering Hebei University of Technology Tianjin 300130 China
Abstract：With the electromagnetic environment becoming more and more complex, the shortcomings 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.
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.
Guo Lei, Liu Dongzhao, Huang Fengrong, Yu Hongli. Research on Disturbance Rejection of Adaptive Spiking Neural Network Based on Synaptic Plasticity under White Gaussian Noise. Transactions of China Electrotechnical Society, 2020, 35(2): 225-235.
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2020, Vol. 35 
