Skip to main content
SpringerLink
Log in

Characteristic analysis of the fractional-order hyperchaotic memristive circuit based on the Wien bridge oscillator

  • Regular Article
  • Published:
The European Physical Journal Plus Aims and scope Submit manuscript

Abstract.

In this paper, a new hyperchaotic memristive circuit based on the Wien bridge oscillator is built. The numerical solution of the new fractional-order memristive system is calculated by using the Adomian decomposition method. By using the spectral entropy (SE) complexity algorithm and the \( C_0\) complexity algorithm, the dynamic characteristics of the fractional-order system are analyzed. Especially, the fractional-order coexisting attractors are found and the coexisting bifurcation diagrams with different order are presented. With varying the order q , the phenomenon of coexisting evolution is observed. Finally, the practical circuit is realized. The results of the theoretical analysis and the numerical simulation show that the fractional-order Wien bridge hyperchaotic memristive circuit system has very complex dynamical characteristics. It provides a theoretical guidance for the chaotic related field.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. L.O. Chua, IEEE Trans. On. Circuit. Theor. 18, 507 (1971)

    Article  Google Scholar 

  2. J.M. Tour, T. He, Nature. 453, 42 (2008)

    Article  ADS  Google Scholar 

  3. L.O. Chua, Appl. Phys. A 102, 765 (2011)

    Article  ADS  Google Scholar 

  4. G. Si, L. Diao, J. Zhu, Nonlinear Dyn. 87, 1 (2016)

    Google Scholar 

  5. J.Y. Ruan, K.H. Sun, J. Mou, Act. Phys. Sin. 19, 19052 (2016)

    Google Scholar 

  6. H. Bao, B.C. Bao, Y. Lin, J. Wang, H.G. Wu, Acta Phys. Sin. 65, 180501 (2016)

    Google Scholar 

  7. C. Li, J.C. Sprott, H. Xing, Nonlinear Dyn. 87, 1355 (2017)

    Google Scholar 

  8. C. Li, J.C. Sprott, H. Xing, Phys. Lett. A 380, 1175 (2016)

    ADS  Google Scholar 

  9. C. Li, W. Hu, J.C. Sprott, X. Wang, Eur. Phys. J. ST 224, 1493 (2015)

    Article  Google Scholar 

  10. C. Li, J.C. Sprott, W. Thio, Phys. Lett. A 379, 890 (2015)

    Google Scholar 

  11. C. Li, J.C. Sprott, Int. J. Bifurc. Chaos 23, 1350199 (2013)

    Article  Google Scholar 

  12. B.C. Bao, J.P. Xu, Z. Liu, S.H. Pan, Sci. Chin. Tech. Sci. 54, 2180 (2011)

    Article  Google Scholar 

  13. I. Vourkas, G.C. Sirakoulis, Nano IEEE Trans. 11, 1151 (2012)

    Article  Google Scholar 

  14. X. Ye, J. Mou, C. Luo, Z. Wang, Nonlinear Dyn. 92, 923 (2018)

    Article  Google Scholar 

  15. S. He, K. Sun, X. Mei, B. Yan, S. Yu, Eur. Phys. J. Plus 132, 36 (2017)

    Article  ADS  Google Scholar 

  16. K. Parand, P. Mazaheri, H. Yousefi, M. Delkhosh, Eur. Phys. J. Plus 132, 77 (2017)

    Article  Google Scholar 

  17. H.H. Wang, K.H. Sun, S.B. He, Int. J. Bifurc. Chaos 25, 1550085 (2015)

    Article  Google Scholar 

  18. M. Li, D. Li, J. Wang, C. Zhao, Isa Trans. 62, 109 (2016)

    Article  Google Scholar 

  19. B.S.T. Alkahtani, A. Atangana, Chaos, Solitons Fractals 89, 539 (2016)

    Article  MathSciNet  ADS  Google Scholar 

  20. G.M. Mahmoud, M.E. Ahmed, T.M. Abed-Elhameed, Eur. Phys. J. Plus 131, 1 (2016)

    Article  Google Scholar 

  21. L. Chen, C. Liu, R. Wu, Y. He, Y. Chai, Neur. Comput. Appl. 27, 549 (2016)

    Article  Google Scholar 

  22. L. Wang, Q. Song, Y. Liu, Z. Zhao, F.E. Alsaadi, Neurocomputing 245, 86 (2017)

    Article  Google Scholar 

  23. H. Wu, X. Zhang, S. Xue, L. Wang, Y. Wang, Neurocomputing 193, 148 (2016)

    Article  Google Scholar 

  24. K. Rajagopal, A. Karthikeyan, A.K. Srinivasan, Nonlinear Dyn. 87, 2281 (2017)

    Article  Google Scholar 

  25. I. Pan, S. Das, Isa Trans. 62, 19 (2016)

    Article  Google Scholar 

  26. A.E. Matouk, A.A. Elsadany, Nonlinear Dyn. 85, 1597 (2016)

    Article  Google Scholar 

  27. G. Adomian, J. Math. Anal. Appl. 113, 202 (1986)

    Article  MathSciNet  Google Scholar 

  28. S. He, K. Sun, H. Wang, Entropy 17, 8308 (2015)

    ADS  Google Scholar 

  29. Y. Wang, K. Sun, S. He, H. Wang, Eur. Phys. J. ST 223, 1598 (2014)

    Article  Google Scholar 

  30. L. Zhang, K. Sun, S. He, H. Wang, Y. Xu, Eur. Phys. J. Plus 132, 31 (2017)

    Article  ADS  Google Scholar 

  31. J. Ruan, K. Sun, J. Mou, S. He, L. Zhang, Eur. Phys. J. Plus 133, 3 (2018)

    Article  Google Scholar 

  32. S. He, K. Sun, H. Wang, X. Mei, Y. Sun, Nonlinear Dyn. 92, 90 (2018)

    Google Scholar 

  33. Z. Wang, M. Yin, T. Zhang, Y. Cai, Y. Wang, Y. Yang, R. Huang, Nanoscale 8, 14015 (2016)

    Article  ADS  Google Scholar 

  34. J. Chen, Z. Zeng, P. Jiang, Neural Netw. 51, 1 (2014)

    Article  Google Scholar 

  35. L. Chen, Y. Chai, R. Wu, T. Ma, H. Zhai, Neurocomputing 111, 192 (2013)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Information Science and Technology, Dalian Maritime University, 116026, Dalian, China

    Xiaolin Ye, Xingyuan Wang, Xiaopeng Yan & Yongjin Xian

  2. School of Information Science and Engineering, Dalian Polytechnic University, 116034, Dalian, China

    Jun Mou

Authors
  1. Xiaolin Ye
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xingyuan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jun Mou
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaopeng Yan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yongjin Xian
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xingyuan Wang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ye, X., Wang, X., Mou, J. et al. Characteristic analysis of the fractional-order hyperchaotic memristive circuit based on the Wien bridge oscillator. Eur. Phys. J. Plus 133, 516 (2018). https://doi.org/10.1140/epjp/i2018-12309-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1140/epjp/i2018-12309-2

Search

Navigation