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Dynamics and implementation of a functional neuron model with hyperchaotic behavior under electromagnetic radiation

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  • Ma, Tao
  • Mou, Jun
  • Chen, Wanzhong

Abstract

Prolonged exposure to electromagnetic radiation (EMR) may be hazardous to human health and plays a key role in the medical diagnosis of some diseases. And this effect can be better demonstrated by constructing a neuron model of EMR. Flux-controlled memristors can estimate the effects of EMR on neurons. In this work, a discrete flux-controlled memristor is used to estimate the behavior of EMR. Furthermore, the memristor is introduced into a neuron model to explore the effects of EMR on the behavior of neurons. The rich and interesting complex dynamical behavior of the model is investigated using analytical methods from nonlinear theory, including plotting bifurcation diagrams, Lyapunov exponent spectra (LEs) and complexity. By modulating the electromagnetic induction strength k of the memristor, it was observed that the introduction of EMR is able to generate hidden hyperchaotic attractors and initial-boosted behavior. The constructed neuron model is implemented based on a DSP platform. Pseudo random number generators (PRNGs) are further designed and the NIST test results illustrate the excellent random performance of the sequences generated by the neuron model. The properties exhibited in the neuron model under EMR provide a reference solution for EMR in the diagnosis and treatment of certain diseases.

Suggested Citation

  • Ma, Tao & Mou, Jun & Chen, Wanzhong, 2025. "Dynamics and implementation of a functional neuron model with hyperchaotic behavior under electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 190(C).
    • Handle: RePEc:eee:chsofr:v:190:y:2025:i:c:s096007792401347x
    DOI: 10.1016/j.chaos.2024.115795
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    References listed on IDEAS

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    1. Zhang, Shaohua & Wang, Cong & Lin, Hairong & Zhang, Hongli & Ma, Ping, 2026. "Offset-controlled plane dynamics in dual memristors-radiated discrete Hopfield neuron," Chaos, Solitons & Fractals, Elsevier, vol. 203(C).
    2. Chen, Chengjie & Gao, Bin & Yu, Yang & Zhao, Shuang & Yang, Yan & Chen, Lianyu & Bao, Han, 2025. "Synchronously adjustable offset boosting and amplitude control in memristive neural network with hardware implementation," Chaos, Solitons & Fractals, Elsevier, vol. 199(P3).
    3. Ding, Dawei & Liu, Xiang & Zhang, Hongwei & Yang, Zongli & Jin, Fan & Chen, Siqi & Zhou, Haitao, 2025. "Reversible image encryption and hiding algorithm based on fractional-order memristive Hopfield neural network," Chaos, Solitons & Fractals, Elsevier, vol. 199(P2).
    4. Shi, Fan & Cao, Yinghong & Xu, Xianying & Banerjee, Santo & Mou, Jun, 2026. "Boosting neural Chaos via memcapacitive electromagnetic radiation in a unidirectional ring neural network," Chaos, Solitons & Fractals, Elsevier, vol. 202(P1).
    5. Ma, Tao & Mou, Jun & Chen, Wanzhong, 2025. "Enriched dynamical behavior of a novel locally active memristor-driven neuron map," Chaos, Solitons & Fractals, Elsevier, vol. 198(C).

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