Quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches | Neural Computing and Applications Skip to main content
Springer Nature Link
Log in

Quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches

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

Abstract

This paper is concerned with quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches. Due to the parameter mismatches, mean-square exponential synchronization generally cannot be achieved directly, then the concept of exponential quasi-synchronization in mean square is introduced. Furthermore, based on the differential inclusions theory, stochastic Lyapunov function method and inequality techniques, some sufficient conditions are derived to guarantee the mean-square exponential quasi-synchronization for stochastic memristor-based neural networks with mixed delays. Finally, two examples are given to show the effectiveness of the proposed 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

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Chua L (1971) Memristor-the missing circuit element. IEEE Trans Circuit Theory 18(5):507–519

    Google Scholar 

  2. Strukov D, Snider G, Stewart D, Williams R (2008) The missing memristor found. Nature 453(7191):80–83

    Google Scholar 

  3. Sharifiy M, Banadaki Y (2010) General spice models for memristor and application to circuit simulation of memristor-based synapses and memory cells. J Circuits Syst Comput 19:407–424

    Google Scholar 

  4. Cantley K, Subramaniam A, Stiegler H, Chapman R, Vogel E (2011) Hebbian learning in spiking neural networks with nanocrystalline silicon TFTs and memristive synapses. IEEE Trans Naontechnol 10:1066–1073

    Google Scholar 

  5. Jo Sh, Chang T, Ebong I, Bhadviya BB, Mazumder P, Lu W (2010) Nanoscale memristor device as synapse in neuromorphic systems. Nano Lett 10:1297–1301

    Google Scholar 

  6. Wu A, Zeng Z, Zhu X, Zhang J (2011) Exponential synchronization of memristor-based recurrent neural networks with time delays. Neurocomputing 74(17):3043–3050

    Google Scholar 

  7. Wu A, Wen S, Zeng Z (2012) Synchronization control of a class of memristor-based recurrent neural networks. Inf Sci 183(1):106–116

    MathSciNet  MATH  Google Scholar 

  8. Wen S, Bao G, Zeng Z, Chen Y, Huang T (2013) Global exponential synchronization of memristor-based recurrent neural networks with time-varying delays. Neural Netw 48:195–203

    MATH  Google Scholar 

  9. Wang L, Shen Y, Yin Q, Zhang G (2015) Adaptive synchronization of memristor-based neural networks with time-varying delays. IEEE Trans Neural Netw Learn Syst 26(9):2033–2042

    MathSciNet  Google Scholar 

  10. Yang X, D WC Ho (2015) Synchronization of delayed memristive neural networks: robust analysis approach. IEEE Trans Cybern 46(10):3377–3387

    Google Scholar 

  11. Cao J, Li R (2017) Fixed-time synchronization of delayed memristor-based recurrent neural networks. Sci China Inf Sci 60(3):032201

    MathSciNet  Google Scholar 

  12. Zhang W, Li C, Huang T, 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

    MathSciNet  Google Scholar 

  13. Guo Z, Shao Y, Wang J (2016) Global synchronization of memristive neural networks subject to random disturbances via distributed pinning control. Neural Netw 84:67–79

    MATH  Google Scholar 

  14. Wen S, Zeng Z, Huang T, Zhang Y (2015) Exponential lag adaptive synchronization of memristive neural networks and applications in pseudo-random generators. IEEE Trans Neural Netw Learn Syst 22(6):1704–1713

    Google Scholar 

  15. Zhang G, Shen Y (2014) Exponential of delayed memristor-based chaotic neural networks via periodically intermittent control. Neural Netw 55:1–10

    MATH  Google Scholar 

  16. Qiu B, Li L, Peng H, Yang Y (2018) Asymptotic and finite-time synchronization of memristor-based switching networks with multi-links and impulsive perturbation. Neural Comput Appl. https://doi.org/10.10071/s00521-017-3312-1

  17. Shi Y, Zhu P (2014) Synchronization of memristive competitive neural networks with different time scales. Neural Comput Appl 25(5):1163–1168

    Google Scholar 

  18. Liu S, Yu Y, Zhang S (2017) Robust synchronization of memristor-based fractional-order Hopfield neural networks with parameter uncertanties. Neural Comput Appl 1:1–10

    Google Scholar 

  19. Wang G, Shen Y (2014) Exponential synchronization of coupled memristive neural networks with time delays. Neural Comput Appl 24(6):1421–1456

    Google Scholar 

  20. Su L, Zhou L (2018) Exponential synchronization of memristor-based recurrent neural networks with multi-proportional delays. Neural Comput Appl. https://doi.org/10.10071/s00521-018-3569-z

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

    Google Scholar 

  22. Jia Q, Tang WKS (2018) Consensus of multi-agents with event-based nonlinear coupling over time-varying digraphs. IEEE Trans Circuits Syst II PP(99):1–5

    Google Scholar 

  23. Jia Q, Tang WKS (2018) Event-triggered protocol for the consensus of multi-agent systems with state-dependent nonlinear coupling. IEEE Trans Circuits Syst I Reg Pap 65(2):723–732

    Google Scholar 

  24. Jia Q, Tang WKS (2012) Consensus of nonlinear agents in directed network with switching topology and communication delay. IEEE Trans Circuits Syst I Reg Pap 59(12):3015–3023

    MathSciNet  Google Scholar 

  25. Yang CY, Li XD, Qiu JL (2017) Output synchronization control with input constraint of complex networks with reaction–diffusion terms. Neural Comput Appl. https://doi.org/10.1007/s00521-017-2892-0. (in press)

  26. Cui B, Zhao CH, Ma TD, Feng C (2016) Leader-following consensus of nonlinear multi-agent systems with switching topologies and unreliable communications. Neural Comput Appl 27:909–915

    Google Scholar 

  27. Huang T, Li C, Liao X (2007) Synchronization of a class of coupled chaotic delayed systems with parameter mismatch. Chaos 17(3):1–5

    MathSciNet  MATH  Google Scholar 

  28. He W, Qian F, Han Q, Cao J (2011) Lag quasi-synchronization of coupled delayed systems with parameter mismatch. IEEE Trans Circuits Syst I 58(6):1345–1357

    MathSciNet  Google Scholar 

  29. Liu X, Chen T, Cao J, Lu W (2011) Dissipativity and quasi-synchronization for networks with discontinuous activations and parameter mismatches. Neural Netw 24(10):1013–1021

    MATH  Google Scholar 

  30. Tang Z, Park J, Feng J (2018) Impulsive effects on quasi-synchornization of neural networks with parameter mismaches and time-varying delays. IEEE Trans Neural Netw Learn Syst 29(4):908–919

    Google Scholar 

  31. Liu C, Li C, Li CJ (2011) Quasi-synchronization of delayed chaotic systems with parameters mimatch and stochastic perturbation. Commun Nonlinear Sci Numer Simul 16:4108–4119

    MathSciNet  MATH  Google Scholar 

  32. Pan L, Cao J (2012) Stochastic quasi-synchronization for delayed dynamical networks via intermittent control. Commun Nonlinear Sci Numer Simul 17:1332–1345

    MathSciNet  MATH  Google Scholar 

  33. Li N, Cao J (2016) Lag synchronization of memristor-based coupled neural networks via \(\omega\)-measure. IEEE Trans Neural Netw Learn Syst 27(3):686–697

    MathSciNet  Google Scholar 

  34. Li N, Cao J, Alsaedi A, Alsaadi F (2017) Lag synchronization criteria for memristor-based coupled neural networks via parameter mismatches analysis approach. Neural Comput 29(6):1721–1744

    MathSciNet  MATH  Google Scholar 

  35. Ding S, Wang Z (2017) Lag quasi-synchronization for memristive neural networks with switching jumps mismatch. Neural Comput Appl 28(12):4011–4022

    Google Scholar 

  36. Xin Y, Li Y, Huang X (2017) Quasi-Synchronization of delayed chaotic memristive neural networks. IEEE Trans Cybern PP(99):1–7

    Google Scholar 

  37. Oshaba AS, Ali ES, Abd-Elazim SM (2015) ACO based speed control of SRM fed by photovoltaic System. Int J Electr Power Energy Syst 67:529–536

    Google Scholar 

  38. Abd-Elazim SM, Ali ES (2016) Load frequency controller design via BAT algorithm for nonlinear interconnected power system. Int J Electr Power Energy Syst 77:166–167

    Google Scholar 

  39. Abd-Elazim SM, Ali ES (2018) Imperialist competitive algorithm for optimal STATCOM design in a multimachine power system. Int J Electr Power Energy Syst 76:136–146

    Google Scholar 

  40. Abd-Elazim SM, Ali ES (2018) Load frequency controller design of a two-area system composing of PV grid and thermal generator via firefly algorithm. Neural Comput Appl 30(2):607–616

    Google Scholar 

  41. Oshaba AS, Ali ES, Abd-Elazim SM (2017) PI controller design using ABC algorithm for MPPT of PV system supplying DC motor pump load. Neural Comput Appl 28(2):353–364

    Google Scholar 

  42. Ali ES, Abd-Elazim SM (2018) Mine blast algorithm for environmental economic load dispatch with valve loading effect. Neural Comput Appl 30(1):261–270

    Google Scholar 

  43. Yang X, Cao J, Qiu J (2015) \(p\)th moment exponential stochastic synchronization of coupled memristor-based neural networks with mixed delays via delayed impulsive control. Neural Netw 65:80–91

    MATH  Google Scholar 

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

    Google Scholar 

  45. Li N, Zheng W (2018) Synchronization criteria for inertial memristor-based neural networks with linear coupling. Neural Netw 106:260–270

    Google Scholar 

  46. Feng J, Chen S, Wang J, Zhao Y (2018) Quasi-synchronization of coupled nonlinear memristive neural networks with time delays by pinning control. IEEE Access 6:26271–26282

    Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Grant Nos. 61503046, 11547006 and 61773401).

Author information

Authors and Affiliations

  1. School of Information and Mathematics, Yangtze University, Jingzhou, 434023, China

    Yinfang Song & Wen Sun

  2. School of Automation, Huazhong University of Science and Technology, Wuhan, 430074, China

    Zhigang Zeng

  3. School of Statistics and Mathematics, Zhongnan University of Economics and Law, Wuhan, 430073, China

    Feng Jiang

Authors
  1. Yinfang Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhigang Zeng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wen Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Feng Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yinfang Song.

Ethics declarations

Conflict of interest

We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, 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.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, Y., Zeng, Z., Sun, W. et al. Quasi-synchronization of stochastic memristor-based neural networks with mixed delays and parameter mismatches. Neural Comput & Applic 32, 4615–4628 (2020). https://doi.org/10.1007/s00521-018-3772-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00521-018-3772-y

Keywords

Search

Navigation