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Synchronization control between two Chua′s circuits via capacitive coupling

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  • Liu, Zhilong
  • Ma, Jun
  • Zhang, Ge
  • Zhang, Yin

Abstract

Nonlinear circuits can generate a variety of oscillations by setting appropriate parameter regions, and periodic oscillation can present distinct periods in the sampled time series for observable variables while chaotic oscillation shows multiple modes in the output variables. Resistor-based voltage coupling benefits the synchronization approach between chaotic circuits even one coupling channel is activated, while consumption of Joule heat in the coupling resistor is inevitable during the realization of synchronization. Complete synchronization is often detected between identical circuits while phase synchronization is mainly reached between non-identical circuits. In this paper, two identical Chua circuits are connected by a capacitor, which the capacitance can be feasibly modulated to support synchronization realization. The mechanism is that the electric field in the coupling capacitor is changed by continuous charge and/discharge on the capacitor plates and energy flow exchange is enhanced to stabilize synchronization between the two chaotic circuits. From physical and experimental view, the capacitance values of coupling capacitor can be modulated by changing the distance and dielectric media between the capacitor plates, thus the coupling intensity is adjusted to change the ability of field energy pumping and exchange. It is found that this kind of electric field coupling can regulate the synchronization stability between dimensionless chaotic systems by applying scale transformation on the chaotic circuits. However, synchronization cannot be stabilized between two non-identical Chua circuits with different parameter regions even when the coupling intensity is increased greatly. The same discussion is also verified in the circuits built on Multisim. As a result, capacitor coupling via one channel can be further applied to control synchronization in neural networks and synchronization realization between neural circuits.

Suggested Citation

  • Liu, Zhilong & Ma, Jun & Zhang, Ge & Zhang, Yin, 2019. "Synchronization control between two Chua′s circuits via capacitive coupling," Applied Mathematics and Computation, Elsevier, vol. 360(C), pages 94-106.
    • Handle: RePEc:eee:apmaco:v:360:y:2019:i:c:p:94-106
    DOI: 10.1016/j.amc.2019.05.004
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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.
    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. Guo, Shengli & Xu, Ying & Wang, Chunni & Jin, Wuyin & Hobiny, Aatef & Ma, Jun, 2017. "Collective response, synapse coupling and field coupling in neuronal network," Chaos, Solitons & Fractals, Elsevier, vol. 105(C), pages 120-127.
    4. Wuyin Jin & Qian Lin & An Wang & Chunni Wang, 2017. "Computer Simulation of Noise Effects of the Neighborhood of Stimulus Threshold for a Mathematical Model of Homeostatic Regulation of Sleep-Wake Cycles," Complexity, Hindawi, vol. 2017, pages 1-7, October.
    5. Ping Zhou & Meihua Ke, 2017. "A New 3D Autonomous Continuous System with Two Isolated Chaotic Attractors and Its Topological Horseshoes," Complexity, Hindawi, vol. 2017, pages 1-7, November.
    6. 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.
    7. Muhammad Iqbal & Muhammad Rehan & Keum-Shik Hong, 2017. "Modeling of inter-neuronal coupling medium and its impact on neuronal synchronization," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-20, May.
    8. 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.
    9. Zhang, Ge & Ma, Jun & Alsaedi, Ahmed & Ahmad, Bashir & Alzahrani, Faris, 2018. "Dynamical behavior and application in Josephson Junction coupled by memristor," Applied Mathematics and Computation, Elsevier, vol. 321(C), pages 290-299.
    10. Wu, Fuqiang & Zhou, Ping & Alsaedi, Ahmed & Hayat, Tasawar & Ma, Jun, 2018. "Synchronization dependence on initial setting of chaotic systems without equilibria," Chaos, Solitons & Fractals, Elsevier, vol. 110(C), pages 124-132.
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    3. Ma, Jun & Xu, Wenkang & Zhou, Ping & Zhang, Ge, 2019. "Synchronization between memristive and initial-dependent oscillators driven by noise," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    4. Yao, Zhao & Wang, Chunni, 2022. "Collective behaviors in a multiple functional network with hybrid synapses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    5. Zhou, Ping & Ma, Jun & Xu, Ying, 2023. "Phase synchronization between neurons under nonlinear coupling via hybrid synapse," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    6. Wang, Chunni & Liu, Zhilong & Hobiny, Aatef & Xu, Wenkang & Ma, Jun, 2020. "Capturing and shunting energy in chaotic Chua circuit," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    7. Yao, Zhao & Zhou, Ping & Alsaedi, Ahmed & Ma, Jun, 2020. "Energy flow-guided synchronization between chaotic circuits," Applied Mathematics and Computation, Elsevier, vol. 374(C).
    8. Jules Tagne Fossi & Vandi Deli & Hélène Carole Edima & Zeric Tabekoueng Njitacke & Florent Feudjio Kemwoue & Jacques Atangana, 2022. "Phase synchronization between two thermo-photoelectric neurons coupled through a Josephson Junction," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 95(4), pages 1-17, April.

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