Journal of Guangxi Normal University(Natural Science Edition) ›› 2020, Vol. 38 ›› Issue (1): 107-113.doi: 10.16088/j.issn.1001-6600.2020.01.014

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Research on Discharge Mode and Synchronization Behavior of Electromagnetic Field Coupled Memristor Neural Network

TAN Anjie, WEI Duqu*, QIN Yinghua   

  1. College of Electronic Engineering, Guangxi Normal University, Guilin Guangxi 541004, China
  • Received:2019-05-15 Online:2020-01-25 Published:2020-01-15

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Abstract: The electrical activity of neurons depends on external stimulation and induced current. Ion crossing cell membrane can induce time-varying magnetic field. In addition, the surface of each cell membrane is regarded as a charged body with complex charge distribution, which generates an induced electric field. Therefore, it is of practical significance to introduce electromagnetic field variables into the traditional neuron model and study the influence of electromagnetic field coupling on the collective dynamics of neural networks. Firstly, a neural network model considering electric field and magnetic field is proposed, in which a magnetic memristor is used to simulate the electromagnetic induction effect in cells and describe the coupling between magnetic flux and membrane potential. Then, through numerical simulation, the influence of electromagnetic induction on the discharge mode conversion and synchronization behavior of neural network is studied. It is found that electric field and magnetic induction can induce the conversion of neuronal electrical activity mode, while synaptic connection can enhance the synchronization behavior of neural network. This paper is innovative for considering the effect of electromagnetic field on neurons. The results of this study may provide new insights into the mechanism of signal coding and transmission in the nervous system.

Key words: neural network, memristor, electric field, synchronization factor

CLC Number: 

  • Q189
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