Skip to main content
SpringerLink
Log in

Synchronization of coupled memristive inertial delayed neural networks with impulse and intermittent control

  • Original Article
  • Published:
Neural Computing and Applications Aims and scope Submit manuscript

Abstract

This paper contributes to the global exponential synchronization under impulses effective and periodically intermittent control for linearly coupled memristive inertial delayed neural networks (MIDNNs). First of all, we built an array of linearly coupled MIDNNs. Second, by using linear matrix inequality, Lyapunov function, comparison principle, and an extended Halanay differential inequality, we derived some conclusions which rely on impulses effects and periodically intermittent control insures the global exponential synchronization of the coupled MIDNNs. In the end, two instances put forward illustrate the feasibility of the theoretical results.

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

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Chua LO (1971) Memristor-the missing circuit element. IEEE Trans Circuit Theory CT 18:507–519

    Article  Google Scholar 

  2. Strukov DB, Snider GS, Stewart DR (2008) The missing memristor found. Nature 453:80–83

    Article  Google Scholar 

  3. Wen SP, Zeng ZG, Huang TW (2014) Exponential adaptive lag synchronization of memristive neural networks via fuzzy method and applications in pseudorandom number generators. IEEE Trans Fuzzy Syst 22(6):1704–1713

    Article  Google Scholar 

  4. Li S, Guo Y (2015) Distributed consensus filter on directed switching graphs. Int Robust Nonlinear Control 25:2019–2040

    Article  MathSciNet  Google Scholar 

  5. Shi YC, Zhu PY (2018) Finite-time synchronization of stochastic memristor-based delayed neural networks. Neural Comput Appl 29(6):293–301

    Article  MathSciNet  Google Scholar 

  6. Meng ZD, Xiang Z (2017) Stability analysis of stochastic memristor-based recurrent neural networks with mixed time-varying delays. Neural Comput Appl 28(7):1787–1799

    Article  Google Scholar 

  7. Zhang GD, Shen Y, Sun J (2012) Global exponential stability of a class of memristor-based recurrent neural networks with time-varying delays. Neurocomputing 97(5):149–154

    Article  Google Scholar 

  8. Jiang P, Zeng Z, Chen J (2015) Almost periodic solutions for a memristor-based neural networks with leakage time-varying and distributed delays. Neural Netw 68:34–45

    Article  Google Scholar 

  9. He X, Li CD, Shu YL (2012) Bogdanov-Takens bifurcation in a single inertial neuron model with delay. Neurocomputing 89:193–201

    Article  Google Scholar 

  10. Li S, Lou YS, Liu B (2014) Bluetooth aided mobile phone localization: a nonlinear neural circuit approach. ACM Trans Embed Comput Syst 13(4):781–7815

    Article  Google Scholar 

  11. Li S, Guo Y (2012) Distributed source seeking by cooperative robots: all-to-all and limited communications, pp 1107–1112

  12. Ouyang DQ, Shao J, Hu C (2019) Stability property of impulsive inertial neural networks with unbounded time delay and saturating actuators. Neural Comput Appl 32:6571–6580

    Article  Google Scholar 

  13. Qin ST, Gu LY, Pan XY (2018) Exponential stability of periodic solution for a memristor-based inertial neural network with time delays. Neural Comput Appl 32:3265–3281

    Article  Google Scholar 

  14. Cao JD, Wan Y (2014) Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays. Neural Netw 53:165–172

    Article  Google Scholar 

  15. Tu ZW, Cao JD, Alsaedi A (2017) Global dissipativity of memristor-based neutral type inertial neural networks. Neural Netw 88:125–133

    Article  Google Scholar 

  16. Li CJ, Yu XH, Yu WW (2016) Distributed event-triggered scheme for economic dispatch in smart grids. IEEE Trans Ind Informatics 12(5):1775–1785

    Article  Google Scholar 

  17. Li S, Guo Y, Bingham B (2014) Multi-robot cooperative control for monitoring and tracking dynamic plumes. In: International conference on robotics and automation, pp 67–73

  18. Li S, Wang Z, Li Y (2013) Using Laplacian eigenmap as heuristic information to solve nonlinear constraints defined on a graph and its application in distributed range-free localization of wireless sensor networks. Neural Process Lett 37(3):411–424

    Article  Google Scholar 

  19. Li CJ, Yu XH, Huang TW (2016) A generalized Hopfield network for nonsmooth constrained convex optimization: lie derivative approach. IEEE Trans Neural Netw Learn Syst 27(2):308–321

    Article  MathSciNet  Google Scholar 

  20. Rakkiyappan R, Kumari EU, Chandrasekar A (2016) Synchronization and periodicity of coupled inertial memristive neural networks with supremums. Neurocomputing 214(19):739–749

    Article  Google Scholar 

  21. Hu JQ, Cao JD, Alofi AE (2015) Pinning synchronization of coupled inertial delayed neural networks. Cognit Neurodyn 9(3):341–350

    Article  Google Scholar 

  22. Guo ZY, Gong SQ, Huang TW (2018) Finite-time synchronization of inertial memristive neural networks with time delay via delay-dependent control. Neurocomputing 293:100–107

    Article  Google Scholar 

  23. Jia Q, Han Z, Tang WKS (2019) Synchronization of multi-agent systems with time-varying control and delayed communications. IEEE Trans Circuits Syst I Regul Pap 66(11):4429–4438

    Article  MathSciNet  Google Scholar 

  24. Jia Q, Sun M, Tang WK (2019) Consensus of multiagent systems with delayed node dynamics and time-varying coupling. IEEE Trans Syst Man Cybern Syst 99:1–10

    Article  Google Scholar 

  25. Zhang GD, Shen Y (2014) Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control. Neural Netw Off J Int Neural Netw Soc 55:1–10

    Article  Google Scholar 

  26. Hu C, Yu J, Jiang HJ (2010) Exponential stabilization and synchronization of neural networks with time-varying delays via periodically intermittent control. Nonlinearity 23(10):2369–2379

    Article  MathSciNet  Google Scholar 

  27. Zhang GD, Shen Y (2014) Exponential stabilization of memristor-based chaotic neural networks with time-varying delays via intermittent control. IEEE Trans Neural Netw Learn Syst 26(7):1431–1441

    Article  MathSciNet  Google Scholar 

  28. Hu B, Guan ZH, Yu XH (2018) Multisynchronization of interconnected memristor-based impulsive neural networks with fuzzy hybrid control. IEEE Trans Fuzzy Syst 26(5):3069–308

    Article  Google Scholar 

  29. Li XF, Fang JN, Li HY (2017) Master-slave exponential synchronization of delayed complex-valued memristor-based neural networks via impulsive control. Neural Netw Off J Int Neural Netw Soc 93:165–175

    Article  Google Scholar 

  30. Zhang W, Li CD, Huang TW, He X (2015) Synchronization of memristor-based coupling recurrent neural networks with time-varying delays and impulses. IEEE Trans Neural Netw Learn Syst 26(12):3308–3313

    Article  MathSciNet  Google Scholar 

  31. Chen WH, Zheng WX (2011) Exponential stability of nonlinear time-delay systems with delayed impulse effects. Automatica 47(5):1075–1083

    Article  MathSciNet  Google Scholar 

  32. Wu QJ, Zhou J, Xiang L (2011) Inpulses-induced exponential stability in recurrent delayed neural networks. Neurocomputing 74:3204–3211

    Article  Google Scholar 

  33. Yang XX, Yang ZC (2013) Synchronization of TS fuzzy complex dynamical networks with time-varying impulsive delays and stochastic effects. Fuzzy Sets Syst 235(1):25–43

    MathSciNet  MATH  Google Scholar 

  34. Zhang W, Li CD, Huang TW (2015) Global stability and synchronization of markovian switching neural networks with stochastic perturbation and impulsive delay. Circuits Syst Signal Process 34(8):2457–2474

    Article  MathSciNet  Google Scholar 

  35. Zhang W, Li CD, Huang TW (2015) Exponential stability of inertial BAM neural networks with time-varying delay via periodically intermittent control. Neural Comput Appl 26(7):1781–1787

    Article  Google Scholar 

  36. Zhang W, Li CD, Huang TW (2016) Stability and synchronization of memristor-based coupling neural networks with time-varying delays via intermittent control. Neurocomputing 173:1066–1072

    Article  Google Scholar 

  37. Zhang HG, Ma TD, Huang GB (2010) Robust global exponential synchronization of uncertain chaotic delayed neural networks via dual-stage impulsive control. IEEE Trans Syst Man Cybern Part B 40(3):831–844

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by Natural Science Foundation of China (Funds No: 61703346) and Fundamental Research Funds for the Central Universities (Grant Nos. XDJK2020TY003, XDJK2019C067).

Author information

Authors and Affiliations

  1. Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing, Department of Electronics and Information Engineering, Southwest University, Chongqing, 400715, China

    Wei Zhang

  2. School of Information Science and Electrical Engineering, Shan Dong Jiaotong University, Jinan, 250357, China

    Jiangtao Qi

Authors
  1. Wei Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiangtao Qi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wei Zhang.

Ethics declarations

Conflicts of interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interest of any nature or kind in any product, service and company that could be construed as influencing the position presented in, or the review of, the manuscript entitled, “Synchronization of coupled memristive inertial delayed neural networks with impulse and intermittent control.”

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, W., Qi, J. Synchronization of coupled memristive inertial delayed neural networks with impulse and intermittent control. Neural Comput & Applic 33, 7953–7964 (2021). https://doi.org/10.1007/s00521-020-05540-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-020-05540-z

Keywords

Search

Navigation