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Synchronization of bursting memristive Josephson junctions via resistive and magnetic coupling

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  • Wu, Fuqiang
  • Guo, Yitong
  • Ma, Jun
  • Jin, Wuyin

Abstract

Some electronic components including memristors and Josephson junctions have potential application to mimic biological neurons or synapses characteristics. In this paper, an equivalent circuit is designed by using two memristive Josephson junctions coupled by a resistor and two inductors. The energy function in an isolated memristive Josephson junction is obtained by using the generalized Hamiltonian formalism. The equivalent circuit can reproduce bursting activities similar with that of neuron by using numerical simulation. Further, the coupling memristive Josephson junctions can reach in-phase and antiphase synchronization under the interplay between resistive and magnetic couplings. The synchronous behaviors are analyzed by discerning the interspike interval of phase difference and average Hamilton energy. The obtained results confirmed the application of Josephson junction in designing bursting neuron-like devices, which are effective to explore dynamics of larger-scale neuromorphic network with different coupling schemes.

Suggested Citation

  • Wu, Fuqiang & Guo, Yitong & Ma, Jun & Jin, Wuyin, 2023. "Synchronization of bursting memristive Josephson junctions via resistive and magnetic coupling," Applied Mathematics and Computation, Elsevier, vol. 455(C).
    • Handle: RePEc:eee:apmaco:v:455:y:2023:i:c:s0096300323003004
    DOI: 10.1016/j.amc.2023.128131
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    References listed on IDEAS

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    1. Ren, Guodong & Xue, Yuxiong & Li, Yuwei & Ma, Jun, 2019. "Field coupling benefits signal exchange between Colpitts systems," Applied Mathematics and Computation, Elsevier, vol. 342(C), pages 45-54.
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    3. Zhou, Ping & Yao, Zhao & Ma, Jun & Zhu, Zhigang, 2021. "A piezoelectric sensing neuron and resonance synchronization between auditory neurons under stimulus," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    4. Baysal, Veli & Yilmaz, Ergin, 2020. "Effects of electromagnetic induction on vibrational resonance in single neurons and neuronal networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
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    Cited by:

    1. Shao, Yan & Wu, Fuqiang & Wang, Qingyun, 2024. "Dynamics and stability of neural systems with indirect interactions involved energy levels," Chaos, Solitons & Fractals, Elsevier, vol. 183(C).

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