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Influences of electromagnetic radiation distribution on chaotic dynamics of a neural network

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  • Lin, Hairong
  • Wang, Chunhua

Abstract

Electromagnetic radiation has an effect on the functional behavior of nervous system, and appropriate electromagnetic radiation is helpful to treat some neurological diseases. In this article, we investigate the effects of electromagnetic radiation distribution on the nonlinear dynamics of a neural network with n neurons. A new mathematical model of the neural network under electromagnetic radiation is developed and analyzed, where electromagnetic radiation is equivalent to the magnetic flux passing through the cell membrane. Chaotic dynamics of the nerve system is detailedly studied by stimulating different number of neurons in the neural network model consisted of three neurons. It is proved that with the increasing of the number of neurons stimulated by electromagnetic radiation, the dynamics behaviors of the neural network gradually change from period moving to chaos, transient chaos and intricate hyperchaos. That is, the dynamical behaviors of the neural system can be modulated through changing the number of neurons affected by electromagnetic radiation in neural network. Therefore, it could give new insights to understand the occurrence mechanism of some neuronal diseases. Moreover, a flexible hardware circuit of the neural network with different electromagnetic radiation distribution is implemented by using commercially available electronic elements, and the experimental measurements are consistent with numerical simulation results.

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  • Lin, Hairong & Wang, Chunhua, 2020. "Influences of electromagnetic radiation distribution on chaotic dynamics of a neural network," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    • Handle: RePEc:eee:apmaco:v:369:y:2020:i:c:s009630031930832x
    DOI: 10.1016/j.amc.2019.124840
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    References listed on IDEAS

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    8. Khodadadi, Vahid & Nowshiravan Rahatabad, Fereidoun & Sheikhani, Ali & Jafarnia Dabanloo, Nader, 2023. "Nonlinear analysis of biceps surface EMG signals for chaotic approaches," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    9. Xiu, Chunbo & Fang, Jingyao & Liu, Yuxia, 2022. "Design and circuit implementation of a novel 5D memristive CNN hyperchaotic system," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    10. Hairong Lin & Chunhua Wang & Fei Yu & Jingru Sun & Sichun Du & Zekun Deng & Quanli Deng, 2023. "A Review of Chaotic Systems Based on Memristive Hopfield Neural Networks," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
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