IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v506y2018icp644-660.html
   My bibliography  Save this article

Synchronization analysis for fractional order memristive Cohen–Grossberg neural networks with state feedback and impulsive control

Author

Listed:
  • Zhang, Lingzhong
  • Yang, Yongqing
  • Xu, Xianyun

Abstract

This paper studies drive response synchronization in fractional order memristive Cohen–Grossberg neural networks (FMCGNNs) with time delay. By applying the asymptotic expansion property of Mittag Leffler function and the definition of average impulsive, some sufficient conditions based on feedback control and impulsive control are established for achieving finite time synchronization and exponential synchronization of the FMCGNNs. Moreover, the selection of impulsive gain depends on the fractional order α. The upper bound of the setting time for synchronization is estimated and the precisely exponential convergence rate is obtained when two controllers are utilized. Finally, numerical simulations illustrate the correctness of the theoretical results for two different controllers.

Suggested Citation

  • Zhang, Lingzhong & Yang, Yongqing & Xu, Xianyun, 2018. "Synchronization analysis for fractional order memristive Cohen–Grossberg neural networks with state feedback and impulsive control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 506(C), pages 644-660.
  • Handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:644-660
    DOI: 10.1016/j.physa.2018.04.088
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437118305168
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2018.04.088?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dmitri B. Strukov & Gregory S. Snider & Duncan R. Stewart & R. Stanley Williams, 2008. "The missing memristor found," Nature, Nature, vol. 453(7191), pages 80-83, May.
    2. James M. Tour & Tao He, 2008. "The fourth element," Nature, Nature, vol. 453(7191), pages 42-43, May.
    3. Wang, Fei & Yang, Yongqing, 2017. "Leader-following exponential consensus of fractional order nonlinear multi-agents system with hybrid time-varying delay: A heterogeneous impulsive method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 158-172.
    4. Mingwen Zheng & Lixiang Li & Haipeng Peng & Jinghua Xiao & Yixian Yang & Hui Zhao & Jingfeng Ren, 2016. "Finite-time synchronization of complex dynamical networks with multi-links via intermittent controls," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-12, February.
    5. Yang, Xujun & Li, Chuandong & Huang, Tingwen & Song, Qiankun, 2017. "Mittag–Leffler stability analysis of nonlinear fractional-order systems with impulses," Applied Mathematics and Computation, Elsevier, vol. 293(C), pages 416-422.
    6. Mingwen Zheng & Lixiang Li & Haipeng Peng & Jinghua Xiao & Yixian Yang & Hui Zhao & Jingfeng Ren, 2016. "Finite-time synchronization of complex dynamical networks with multi-links via intermittent controls," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 89(2), pages 1-12, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pratap, A. & Raja, R. & Cao, J. & Lim, C.P. & Bagdasar, O., 2019. "Stability and pinning synchronization analysis of fractional order delayed Cohen–Grossberg neural networks with discontinuous activations," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 241-260.
    2. Zhang, Hai & Chen, Xinbin & Ye, Renyu & Stamova, Ivanka & Cao, Jinde, 2023. "Adaptive quasi-synchronization analysis for Caputo delayed Cohen–Grossberg neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 212(C), pages 49-65.
    3. Ravi Agarwal & Snezhana Hristova, 2022. "Impulsive Memristive Cohen–Grossberg Neural Networks Modeled by Short Term Generalized Proportional Caputo Fractional Derivative and Synchronization Analysis," Mathematics, MDPI, vol. 10(13), pages 1-12, July.
    4. Zhang, Yanlin & Deng, Shengfu, 2019. "Finite-time projective synchronization of fractional-order complex-valued memristor-based neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 176-190.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhou, Ya & Wan, Xiaoxiao & Huang, Chuangxia & Yang, Xinsong, 2020. "Finite-time stochastic synchronization of dynamic networks with nonlinear coupling strength via quantized intermittent control," Applied Mathematics and Computation, Elsevier, vol. 376(C).
    2. Usa Humphries & Grienggrai Rajchakit & Pramet Kaewmesri & Pharunyou Chanthorn & Ramalingam Sriraman & Rajendran Samidurai & Chee Peng Lim, 2020. "Stochastic Memristive Quaternion-Valued Neural Networks with Time Delays: An Analysis on Mean Square Exponential Input-to-State Stability," Mathematics, MDPI, vol. 8(5), pages 1-26, May.
    3. Chen, Xiao-Long & Wang, Rui-Jie & Yang, Chun & Cai, Shi-Min, 2019. "Hybrid resource allocation and its impact on the dynamics of disease spreading," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 156-165.
    4. Xu, Wei & Zhu, Song & Fang, Xiaoyu & Wang, Wei, 2019. "Adaptive anti-synchronization of memristor-based complex-valued neural networks with time delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    5. Zhang, Chuan & Wang, Xingyuan & Luo, Chao & Li, Junqiu & Wang, Chunpeng, 2018. "Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 251-264.
    6. Mathiyalagan, K. & Park, Ju H. & Sakthivel, R., 2015. "Synchronization for delayed memristive BAM neural networks using impulsive control with random nonlinearities," Applied Mathematics and Computation, Elsevier, vol. 259(C), pages 967-979.
    7. Huaiqin Wu & Luying Zhang & Sanbo Ding & Xueqing Guo & Lingling Wang, 2013. "Complete Periodic Synchronization of Memristor-Based Neural Networks with Time-Varying Delays," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-12, July.
    8. Wang, Cong & Zhang, Hongli & Fan, Wenhui & Ma, Ping, 2018. "Adaptive control method for chaotic power systems based on finite-time stability theory and passivity-based control approach," Chaos, Solitons & Fractals, Elsevier, vol. 112(C), pages 159-167.
    9. Min, Fuhong & Zhang, Wen & Ji, Ziyi & Zhang, Lei, 2021. "Switching dynamics of a non-autonomous FitzHugh-Nagumo circuit with piecewise-linear flux-controlled memristor," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    10. Luo, Mengzhuo & Cheng, Jun & Liu, Xinzhi & Zhong, Shouming, 2019. "An extended synchronization analysis for memristor-based coupled neural networks via aperiodically intermittent control," Applied Mathematics and Computation, Elsevier, vol. 344, pages 163-182.
    11. Liu, Shuxin & Yu, Yongguang & Zhang, Shuo & Zhang, Yuting, 2018. "Robust stability of fractional-order memristor-based Hopfield neural networks with parameter disturbances," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 845-854.
    12. Sakthivel, R. & Anbuvithya, R. & Mathiyalagan, K. & Ma, Yong-Ki & Prakash, P., 2016. "Reliable anti-synchronization conditions for BAM memristive neural networks with different memductance functions," Applied Mathematics and Computation, Elsevier, vol. 275(C), pages 213-228.
    13. Bao, Haibo & Park, Ju H. & Cao, Jinde, 2015. "Matrix measure strategies for exponential synchronization and anti-synchronization of memristor-based neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 543-556.
    14. Chang, Wenting & Zhu, Song & Li, Jinyu & Sun, Kaili, 2018. "Global Mittag–Leffler stabilization of fractional-order complex-valued memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 346-362.
    15. Long, Linbo & Zhong, Kan & Wang, Wei, 2018. "Malicious viruses spreading on complex networks with heterogeneous recovery rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 509(C), pages 746-753.
    16. Yang, Shuai & Hu, Cheng & Yu, Juan & Jiang, Haijun, 2021. "Projective synchronization in finite-time for fully quaternion-valued memristive networks with fractional-order," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    17. Yuan, Manman & Wang, Weiping & Luo, Xiong & Liu, Linlin & Zhao, Wenbing, 2018. "Finite-time anti-synchronization of memristive stochastic BAM neural networks with probabilistic time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 113(C), pages 244-260.
    18. Hongguang Fan & Yue Rao & Kaibo Shi & Hui Wen, 2023. "Global Synchronization of Fractional-Order Multi-Delay Coupled Neural Networks with Multi-Link Complicated Structures via Hybrid Impulsive Control," Mathematics, MDPI, vol. 11(14), pages 1-17, July.
    19. Shi, Yanchao & Cao, Jinde & Chen, Guanrong, 2017. "Exponential stability of complex-valued memristor-based neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 313(C), pages 222-234.
    20. Jin-E Zhang & Huan Liu, 2019. "Global Robust Exponential Synchronization of Multiple Uncertain Neural Networks Subject to Event-Triggered Strategy," Complexity, Hindawi, vol. 2019, pages 1-16, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:506:y:2018:i:c:p:644-660. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.