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Initial condition-offset regulating synchronous dynamics and energy diversity in a memristor-coupled network of memristive HR neurons

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  • Bao, Han
  • Yu, Xihong
  • Zhang, Yunzhen
  • Liu, Xiaofeng
  • Chen, Mo

Abstract

Memristors can be thought of as special connection synapses with internal states that regulate synchronous behavior or energy propagation between neurons in a neural network. By connecting two memristive Hindmarsh-Rose (mHR) neurons with one memristor coupling, this paper synthesizes a memristor-coupled mHR neuron (MC-mHRN) network without equilibrium point. For this network, the synchronization condition regulated by the initial condition-offset (ICO) of the memristive channel are derived theoretically, and the ICO-regulating synchronous dynamics is evaluated numerically. Furthermore, the Hamiltonian energy of mHR neuron is studied by Helmholtz's theorem, and the ICO-regulating energy diversity is analyzed numerically. It is demonstrated that the coupling strength and initial condition of the memristive channel can regulate the synchronous dynamics and energy diversity in the MC-mHRN network, thus achieving complete synchronization as well as energy balance. Consequently, the two mHR neurons in hidden chaotic firing modes deliver field energy via memristive channel until the fully synchronized energy balance is achieved. In addition, a digital platform of the MC-mHRN network is fabricated, and the experimental results validate the numerical ones of the synchronous dynamics.

Suggested Citation

  • Bao, Han & Yu, Xihong & Zhang, Yunzhen & Liu, Xiaofeng & Chen, Mo, 2023. "Initial condition-offset regulating synchronous dynamics and energy diversity in a memristor-coupled network of memristive HR neurons," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:chsofr:v:177:y:2023:i:c:s096007792301069x
    DOI: 10.1016/j.chaos.2023.114167
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    1. Megam Ngouonkadi, E.B. & Fotsin, H.B. & Louodop Fotso, P. & Kamdoum Tamba, V. & Cerdeira, Hilda A., 2016. "Bifurcations and multistability in the extended Hindmarsh–Rose neuronal oscillator," Chaos, Solitons & Fractals, Elsevier, vol. 85(C), pages 151-163.
    2. Mostaghimi, Soudeh & Nazarimehr, Fahimeh & Jafari, Sajad & Ma, Jun, 2019. "Chemical and electrical synapse-modulated dynamical properties of coupled neurons under magnetic flow," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 42-56.
    3. Yu, Xihong & Bao, Han & Chen, Mo & Bao, Bocheng, 2023. "Energy balance via memristor synapse in Morris-Lecar two-neuron network with FPGA implementation," Chaos, Solitons & Fractals, Elsevier, vol. 171(C).
    4. Li, Kexin & Bao, Bocheng & Ma, Jun & Chen, Mo & Bao, Han, 2022. "Synchronization transitions in a discrete memristor-coupled bi-neuron model," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    5. Bao, Han & Ding, Ruoyu & Chen, Bei & Xu, Quan & Bao, Bocheng, 2023. "Two-dimensional non-autonomous neuron model with parameter-controlled multi-scroll chaotic attractors," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Njitacke, Zeric Tabekoueng & Takembo, Clovis Ntahkie & Awrejcewicz, Jan & Fouda, Henri Paul Ekobena & Kengne, Jacques, 2022. "Hamilton energy, complex dynamical analysis and information patterns of a new memristive FitzHugh-Nagumo neural network," Chaos, Solitons & Fractals, Elsevier, vol. 160(C).
    7. Chen, Xiongjian & Wang, Ning & Wang, Yiteng & Wu, Huagan & Xu, Quan, 2023. "Memristor initial-offset boosting and its bifurcation mechanism in a memristive FitzHugh-Nagumo neuron model with hidden dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    8. Xu, Ying & Jia, Ya & Ma, Jun & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Synchronization between neurons coupled by memristor," Chaos, Solitons & Fractals, Elsevier, vol. 104(C), pages 435-442.
    9. Parastesh, Fatemeh & Azarnoush, Hamed & Jafari, Sajad & Hatef, Boshra & Perc, Matjaž & Repnik, Robert, 2019. "Synchronizability of two neurons with switching in the coupling," Applied Mathematics and Computation, Elsevier, vol. 350(C), pages 217-223.
    10. Wu, Fuqiang & Wang, Chunni & Jin, Wuyin & Ma, Jun, 2017. "Dynamical responses in a new neuron model subjected to electromagnetic induction and phase noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 81-88.
    11. Anthony M. Zador, 2019. "A critique of pure learning and what artificial neural networks can learn from animal brains," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    12. Bocheng Bao & Aihuang Hu & Han Bao & Quan Xu & Mo Chen & Huagan Wu, 2018. "Three-Dimensional Memristive Hindmarsh–Rose Neuron Model with Hidden Coexisting Asymmetric Behaviors," Complexity, Hindawi, vol. 2018, pages 1-11, February.
    13. Ma, Jun & Mi, Lv & Zhou, Ping & Xu, Ying & Hayat, Tasawar, 2017. "Phase synchronization between two neurons induced by coupling of electromagnetic field," Applied Mathematics and Computation, Elsevier, vol. 307(C), pages 321-328.
    14. Liu, Yong & Ren, Guodong & Zhou, Ping & Hayat, Tasawar & Ma, Jun, 2019. "Synchronization in networks of initially independent dynamical systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 370-380.
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