Antiinterference Function of Scale-Free Spiking Neural Network Under AC Magnetic Field Stimulation

Abstract

The complexity and changeability of electromagnetic environment make the deficiency of traditional methods of electromagnetic protection increasingly prominent. The organisms with the regulation of nervous system have advantages of self-adaptive, self-organizing, and self-repairing. Therefore, it is necessary to explore a new thought on electromagnetic protection by drawing from the biological self-adaptive advantage. In this study, two kinds of scale-free spiking neural networks (sfSNNs) with different clustering coefficients are constructed. Then, the antiinterference function of the sfSNNs under the ac magnetic field stimulation is evaluated and compared. Finally, the antiinterference mechanism is analyzed. The experimental results show that both sfSNNs have a certain antiinterference function, and the performance of the sfSNN with high clustering coefficient is better than that with low clustering coefficient in the antiinterference function; the dynamic evolution of neural information processing in the sfSNN is clarified; and the dynamic regulation of synaptic plasticity is the intrinsic factor of the antiinterference function of the sfSNNs. This study lays a theoretical foundation for the electromagnetic protection of electronic system based on adaptive bionic mechanism.