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Resonance synchronisation between memristive oscillators and network without variable coupling

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Abstract

Continuous energy pumping and exchange along the coupling channel can balance the energy release between nonlinear oscillators for reaching complete synchronisation. When external stimulus is applied, energy is injected and encoded for regulating the dynamics of nonlinear oscillators and circuits. In this paper, the synchronisation between memristive Rössler oscillators is investigated by reactivating one memristive variable, and external stimuli are changed to detect the occurrence of synchronisation without direct variable coupling. In the presence of periodical stimulus, stochastic switch and feedback on the memristive variable can induce synchronisation between two memristive oscillators and chain network composed of memristive oscillators. In the presence of noise, stochastic feedback and disturbance on the memristive variable can keep synchronisation stable between two oscillators, and complete synchronisation is realised. In addition, the synchronisation factor and spatial patterns are calculated to confirm the occurrence of synchronisation between more chaotic oscillators when memristive function is activated even when no coupling channels are switched on.

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References

  1. Z Yao et al, Appl. Math. Comput. 374, 124998 (2020)

    MathSciNet  Google Scholar 

  2. C Wang et al, Euro. Phys. J. Special Topics 228(10),1907 (2019)

    Article  ADS  Google Scholar 

  3. A Chanthbouala et al, Nature Mater. 11(10), 860 (2012)

    Article  ADS  Google Scholar 

  4. C Yakopcic et al, IEEE Electron Dev. Lett. 32(10),1436 (2011)

    Article  ADS  Google Scholar 

  5. B Muthuswamy, Int. J. Bifurc. Chaos 20, 1335 (2010)

    Article  Google Scholar 

  6. Z I Mannan et al, Nonlinear Dyn. 99, 3169 (2020)

    Article  Google Scholar 

  7. X Ye et al, Nonlinear Dyn. 99, 1489 (2020)

    Article  Google Scholar 

  8. N Wang et al, Nonlinear Dyn. 97, 1477 (2019)

    Article  Google Scholar 

  9. B Bao et al, Nonlinear Dyn. 99, 2339 (2020)

    Article  Google Scholar 

  10. H Bao et al, Nonlinear Dyn. 100, 937 (2020)

    Article  Google Scholar 

  11. H M Deng and Q H Wang, Pramana – J. Phys. 93(3): 49 (2019)

    Google Scholar 

  12. G Zhang et al, Appl. Math. Comput. 321, 290 (2018)

    MathSciNet  Google Scholar 

  13. Y Xu et al, Appl. Math. Comput. 385, 125427 (2020)

    MathSciNet  Google Scholar 

  14. X F Zhang et al, Mod. Phys. Lett. B 34, 2050267 (2020)

    Article  ADS  Google Scholar 

  15. Y Zhang et al, Sci. China Technol. Sci. 63, 2328 (2020)

  16. Z Liu et al, Appl. Math. Comput. 360, 94 (2019)

    Article  MathSciNet  Google Scholar 

  17. Y Xu et al, Front. Inform. Technol. Electron. Eng. 20, 571 (2019)

    Google Scholar 

  18. Z Liu et al, Nonlinear Dyn. 97, 2661 (2019)

    Article  Google Scholar 

  19. Z Yao et al, Nonlinear Dyn. 96, 205 (2019)

    Article  Google Scholar 

  20. S Zhu et al, Chin. J. Phys. 62, 9 (2019)

    Article  Google Scholar 

  21. P D Pinto et al, EPL 117, 50009 (2017)

    Article  ADS  Google Scholar 

  22. J A Eaton et al, Phys. Rev. E 94, 032207 (2016)

    Article  ADS  Google Scholar 

  23. A Mizrahi et al, Phys. Rev. B 94, 054419 (2016)

    Article  ADS  Google Scholar 

  24. Y Wan et al, Phys. Rev. E 81, 036201 (2010)

    Article  ADS  Google Scholar 

  25. S Hata et al, Phys. Rev. E 82, 036206 (2010)

    Article  ADS  MathSciNet  Google Scholar 

  26. D H He et al, Phys. Rev. E 67, 027201 (2003)

    Article  ADS  Google Scholar 

  27. Y Wu et al, Chin. Phys. Lett. 24, 3066 (2007)

    Article  ADS  Google Scholar 

  28. Y Wu et al, Chaos Solitons Fractals 23, 1605 (2005)

    Article  ADS  MathSciNet  Google Scholar 

  29. C Wang et al, Chaos Solitons Fractals 134, 109697 (2020)

    Article  MathSciNet  Google Scholar 

  30. J Ma et al, Appl. Math. Comput. 298, 65 (2017)

    MathSciNet  Google Scholar 

  31. J Ma et al, Physica A 536, 122598 (2019)

    Article  MathSciNet  Google Scholar 

  32. F Q Wu et al, J. Zhejiang Univ. Sci. A 19, 889 (2018)

    Article  Google Scholar 

  33. D Gonze et al, Biophys. J. 89,120 (2005)

    Article  ADS  Google Scholar 

  34. B K Bera et al, Chaos 29, 053115 (2019)

    Article  ADS  MathSciNet  Google Scholar 

  35. N Burić et al, Phys. Rev. E 78, 036211 (2008)

    Article  ADS  Google Scholar 

  36. N Kopell and B Ermentrout, PNAS 101(43), 15482 (2004)

    Article  ADS  Google Scholar 

  37. D G Fan and Q Y Wang, Sci. China Technol. Sci. 60, 1019 (2017)

    Article  ADS  Google Scholar 

  38. W W Xiao et al, Sci. China Technol. Sci. 59, 1943 (2016)

    Article  ADS  Google Scholar 

  39. J Ma et al, J. Zhejiang Univ. Sci. A 20, 639 (2019)

    Article  Google Scholar 

  40. M Lv et al, Sci. China Technol. Sci. 62, 448 (2019)

    Article  ADS  Google Scholar 

  41. S Ma et al, AEU-Int. J. Electron. Commun. 105, 177 (2019)

    Google Scholar 

  42. K Usha and P A Subha, Nonlinear Dyn. 96, 2115 (2019)

    Article  Google Scholar 

  43. Y Xu et al, Nonlinear Dyn. 95, 3237 (2019)

    Article  Google Scholar 

  44. H X Qin et al, Physica A 501,141 (2018)

    Article  ADS  MathSciNet  Google Scholar 

  45. J Ma et al, Int. J. Mod. Phys. B 31, 1650251 (2017)

    Article  ADS  Google Scholar 

  46. S Nakamura and K Tateno, Cogn. Neurodyn. 13, 303 (2019)

    Article  Google Scholar 

  47. A Ray et al, Physica A 392, 4837 (2013)

    Article  ADS  MathSciNet  Google Scholar 

  48. S Majhi et al, Euro. Phys. J. Special Topics 225, 65 (2016)

    Article  ADS  Google Scholar 

  49. D Ghosh et al, Phys. Lett. A 374, 2143 (2010)

    Article  ADS  Google Scholar 

  50. P Chakraborty and S Poria, Pramana – J. Phys. 93(2): 19 (2019)

    Google Scholar 

  51. S T Kingni et al, Pramana – J. Phys. 93(1): 12 (2019)

    Google Scholar 

Download references

Acknowledgements

This project is supported by the National Natural Science Foundation of China under Grant Nos 11765011 and 12072139.

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Correspondence to Jun Ma.

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Zhang, Y., Zhou, P., Yao, Z. et al. Resonance synchronisation between memristive oscillators and network without variable coupling. Pramana - J Phys 95, 49 (2021). https://doi.org/10.1007/s12043-020-02073-x

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  • DOI: https://doi.org/10.1007/s12043-020-02073-x

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