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Enriched dynamical behavior of a novel locally active memristor-driven neuron map

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

Abstract

The construction of neuron models using memristors with bionic properties can provide new ideas for brain-like research. This paper proposes a novel discrete locally active memristor (DLAM) designed to drive neuron map to generate complex chaotic dynamics. The nonvolatility and locally active properties of the proposed memristor are exhaustively investigated. The bifurcation behavior is analyzed by varying the DLAM-dependent parameters and interesting Feigenbaum remerging trees are found. Moreover, the variation of the memristor parameters is capable of triggering multistability and generating complex heterogeneous coexistence. Adjusting the initial conditions of the memristor was able to induce offset-boosted coexistence with a hybrid topology. Finally, a pseudo random sequence generator (PRNG) is designed using chaotic sequences generated by DLAM-driven neuron map and shows excellent performance. A DSP experimental platform was built for numerical simulation verification. The novel DLAM is proposed to provide new insights for the study of nonlinear behavior in neuron models.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:198:y:2025:i:c:s0960077925005508
    DOI: 10.1016/j.chaos.2025.116537
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    References listed on IDEAS

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    1. Lai, Qiang & Yang, Liang & Liu, Yuan, 2022. "Design and realization of discrete memristive hyperchaotic map with application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 165(P1).
    2. Ma, Tao & Mou, Jun & Banerjee, Santo & Cao, Yinghong, 2023. "Analysis of the functional behavior of fractional-order discrete neuron under electromagnetic radiation," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
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    4. Zhao, Qianhan & Bao, Han & Zhang, Xi & Wu, Huagan & Bao, Bocheng, 2024. "Complexity enhancement and grid basin of attraction in a locally active memristor-based multi-cavity map," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).
    5. Lai, Qiang & Yang, Liang, 2023. "Discrete memristor applied to construct neural networks with homogeneous and heterogeneous coexisting attractors," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    6. Fan, Chunlei & Ding, Qun, 2025. "Design and dynamic analysis of a class of new 3-D discrete memristive hyperchaotic maps with multi-type hidden attractors," Chaos, Solitons & Fractals, Elsevier, vol. 191(C).
    7. Wang, Mengjiao & Yi, Zou & Li, Zhijun, 2025. "A memristive Ikeda map and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 190(C).
    8. Wang, Chunhua & Li, Yufei & Deng, Quanli, 2025. "Discrete-time fractional-order local active memristor-based Hopfield neural network and its FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 193(C).
    9. Mao, Yidan & Dong, Yujiao & Lu, Zhenzhou & Xiang, Chenyang & Wang, Jinqi & Liang, Yan, 2025. "Second-order locally active memristor based neuronal circuit," Chaos, Solitons & Fractals, Elsevier, vol. 195(C).
    10. 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).
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