IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i13p2906-d1182130.html
   My bibliography  Save this article

Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control

Author

Listed:
  • Beibei Guo

    (School of Mathematical Sciences, Hebei Normal University, Shijiazhuang 050024, China)

  • Yu Xiao

    (Department of Mathematics, Harbin Institute of Technology, Harbin 150001, China)

Abstract

In this paper, the issue of exponential synchronization in Markov switching inertial neural networks with mixed delays is investigated via aperiodically on–off adaptive control. The inertial term is considered, which extends the existing network modes with first-order differential term. Combined with the Lyapunov method, graph theory, and the differential inequalities technique, two types of synchronization criteria are presented which take into account all of the time delay information and reduce the conservativeness. Finally, some numerical simulations are provided in order to show the validity of the theoretical results.

Suggested Citation

  • Beibei Guo & Yu Xiao, 2023. "Synchronization of Markov Switching Inertial Neural Networks with Mixed Delays under Aperiodically On-Off Adaptive Control," Mathematics, MDPI, vol. 11(13), pages 1-15, June.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:13:p:2906-:d:1182130
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/13/2906/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/13/2906/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Feng, Jiqiang & Li, Yongcai & Zhang, Yingfang & Xu, Chen, 2023. "Stabilization of multi-link delayed neutral-type complex networks with jump diffusion via aperiodically intermittent control," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    2. Zhang, Jianmei & Wu, Jianwei & Bao, Haibo & Cao, Jinde, 2018. "Synchronization analysis of fractional-order three-neuron BAM neural networks with multiple time delays," Applied Mathematics and Computation, Elsevier, vol. 339(C), pages 441-450.
    Full references (including those not matched with items on IDEAS)

    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. Qi, Xingnan & Bao, Haibo & Cao, Jinde, 2019. "Exponential input-to-state stability of quaternion-valued neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 358(C), pages 382-393.
    2. Zhen Yang & Zhengqiu Zhang, 2022. "Finite-Time Synchronization Analysis for BAM Neural Networks with Time-Varying Delays by Applying the Maximum-Value Approach with New Inequalities," Mathematics, MDPI, vol. 10(5), pages 1-16, March.
    3. Syed Ali, M. & Narayanan, Govindasamy & Shekher, Vineet & Alsulami, Hamed & Saeed, Tareq, 2020. "Dynamic stability analysis of stochastic fractional-order memristor fuzzy BAM neural networks with delay and leakage terms," Applied Mathematics and Computation, Elsevier, vol. 369(C).
    4. Du, Feifei & Lu, Jun-Guo, 2021. "New criterion for finite-time synchronization of fractional order memristor-based neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    5. Luo, Yiping & Yao, Yuejie & Cheng, Zifeng & Xiao, Xing & Liu, Hanyu, 2021. "Event-triggered control for coupled reaction–diffusion complex network systems with finite-time synchronization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 562(C).
    6. Lin, Shanrong & Liu, Xiwei, 2023. "Synchronization and control for directly coupled reaction–diffusion neural networks with multiweights and hybrid coupling," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    7. Li, Hui & Kao, YongGui & Stamova, Ivanka & Shao, Chuntao, 2021. "Global asymptotic stability and S-asymptotic ω-periodicity of impulsive non-autonomous fractional-order neural networks," Applied Mathematics and Computation, Elsevier, vol. 410(C).
    8. Pahnehkolaei, Seyed Mehdi Abedi & Alfi, Alireza & Machado, J.A. Tenreiro, 2019. "Delay independent robust stability analysis of delayed fractional quaternion-valued leaky integrator echo state neural networks with QUAD condition," Applied Mathematics and Computation, Elsevier, vol. 359(C), pages 278-293.
    9. Jia, You & Wu, Huaiqin & Cao, Jinde, 2020. "Non-fragile robust finite-time synchronization for fractional-order discontinuous complex networks with multi-weights and uncertain couplings under asynchronous switching," Applied Mathematics and Computation, Elsevier, vol. 370(C).
    10. Zhang, Weiwei & Zhang, Hai & Cao, Jinde & Zhang, Hongmei & Chen, Dingyuan, 2020. "Synchronization of delayed fractional-order complex-valued neural networks with leakage delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 556(C).

    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:gam:jmathe:v:11:y:2023:i:13:p:2906-:d:1182130. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.