IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v477y2024ics0096300324002613.html
   My bibliography  Save this article

Lagrange stability and passivity in the mean square sense of discrete-time stochastic Markovian switched neural networks with time-varying mixed delays

Author

Listed:
  • Yang, Liu
  • Ma, Weijun
  • Wang, Xin

Abstract

In this paper, the Lagrange stability and passivity of a class of discrete-time stochastic Markovian switching neural networks with mixed delays are studied. The mixed delays include time-varying transmission and distribution delays. Global exponential Lagrange stability criterion and passivity criterion in the mean square sense are derived. A numerical example illustrates the usefulness of these criteria. The originality of the proposed method lies in: (i) the criteria are derived directly from the definitions rather than constructing Lyapunov–Krasovskii functional; (ii) the inequalities in the criteria contain only a few decision variables, which is easy to solve and leads to low computational complexity.

Suggested Citation

  • Yang, Liu & Ma, Weijun & Wang, Xin, 2024. "Lagrange stability and passivity in the mean square sense of discrete-time stochastic Markovian switched neural networks with time-varying mixed delays," Applied Mathematics and Computation, Elsevier, vol. 477(C).
    • Handle: RePEc:eee:apmaco:v:477:y:2024:i:c:s0096300324002613
    DOI: 10.1016/j.amc.2024.128800
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300324002613
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2024.128800?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. Chen, Yonghui & Xue, Yu & Yang, Xiaona & Zhang, Xian, 2023. "A direct analysis method to Lagrangian global exponential stability for quaternion memristive neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 439(C).
    2. Jiao, Shiyu & Shen, Hao & Wei, Yunliang & Huang, Xia & Wang, Zhen, 2018. "Further results on dissipativity and stability analysis of Markov jump generalized neural networks with time-varying interval delays," Applied Mathematics and Computation, Elsevier, vol. 336(C), pages 338-350.
    3. Dong, Zeyu & Wang, Xin & Zhang, Xian, 2020. "A nonsingular M-matrix-based global exponential stability analysis of higher-order delayed discrete-time Cohen–Grossberg neural networks," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    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. Hua, Wentao & Wang, Yantao & Liu, Chunyan, 2024. "New method for global exponential synchronization of multi-link memristive neural networks with three kinds of time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 471(C).
    2. Zheng, Wei & Zhang, Zhiming & Lam, Hak-Keung & Sun, Fuchun & Wen, Shuhuan, 2023. "LMIs-based exponential stabilization for interval delay systems via congruence transformation: Application in chaotic Lorenz system," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Jiao, Ticao & Zong, Guangdeng & Pang, Guochen & Zhang, Housheng & Jiang, Jishun, 2020. "Admissibility analysis of stochastic singular systems with Poisson switching," Applied Mathematics and Computation, Elsevier, vol. 386(C).
    4. Sakthivel, Ramalingam & Sakthivel, Rathinasamy & Kwon, Oh-Min & Selvaraj, Palanisamy, 2021. "Disturbance rejection for singular semi-Markov jump neural networks with input saturation," Applied Mathematics and Computation, Elsevier, vol. 407(C).
    5. 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.
    6. Shi, Kaibo & Wang, Jun & Zhong, Shouming & Zhang, Xiaojun & Liu, Yajuan & Cheng, Jun, 2019. "New reliable nonuniform sampling control for uncertain chaotic neural networks under Markov switching topologies," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 169-193.
    7. Li, Wenhua & Gao, Xingbao & Li, Ruoxia, 2020. "Stability and synchronization control of inertial neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 367(C).
    8. Wang, Jing & Hu, Xiaohui & Wei, Yunliang & Wang, Zhen, 2019. "Sampled-data synchronization of semi-Markov jump complex dynamical networks subject to generalized dissipativity property," Applied Mathematics and Computation, Elsevier, vol. 346(C), pages 853-864.
    9. Nguyen, Cuong M. & Pathirana, Pubudu N. & Trinh, Hieu, 2019. "Robust observer and observer-based control designs for discrete one-sided Lipschitz systems subject to uncertainties and disturbances," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 42-53.
    10. Meng, Xianhe & Zhang, Xian & Wang, Yantao, 2023. "Bounded real lemmas and exponential H∞ control for memristor-based neural networks with unbounded time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 210(C), pages 66-81.
    11. Xu, Bo & Liang, Yanjun & Li, Yuan-Xin & Hou, Zhongsheng, 2022. "Adaptive command filtered fixed-time control of nonlinear systems with input quantization," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    12. Chen, Yonghui & Zhang, Xian & Xue, Yu, 2022. "Global exponential synchronization of high-order quaternion Hopfield neural networks with unbounded distributed delays and time-varying discrete delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 173-189.
    13. Yao, Dajie & Dou, Chunxia & Xie, Xiangpeng & Hu, Songlin, 2022. "Containment control of non-affine multi-agent systems based on given precision," Applied Mathematics and Computation, Elsevier, vol. 412(C).
    14. Huang, Zhengguo & Xia, Jianwei & Wang, Jing & Wei, Yunliang & Wang, Zhen & Wang, Jian, 2019. "Mixed H∞/l2−l∞ state estimation for switched genetic regulatory networks subject to packet dropouts: A persistent dwell-time switching mechanism," Applied Mathematics and Computation, Elsevier, vol. 355(C), pages 198-212.
    15. Huang, Chengdai & Liu, Heng & Chen, Xiaoping & Cao, Jinde & Alsaedi, Ahmed, 2020. "Extended feedback and simulation strategies for a delayed fractional-order control system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    16. Wang, Xuelian & Xia, Jianwei & Wang, Jing & Wang, Jian & Wang, Zhen, 2019. "Passive state estimation for fuzzy jumping neural networks with fading channels based on the hidden Markov model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    17. Dai, Mingcheng & Huang, Zhengguo & Xia, Jianwei & Meng, Bo & Wang, Jian & Shen, Hao, 2019. "Non-fragile extended dissipativity-based state feedback control for 2-D Markov jump delayed systems," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    18. Chang, Xu-Kang & He, Yong, 2024. "Reachable set estimation of delayed Markovian jump neural networks via variables-augmented-based free-weighting-matrices method," Applied Mathematics and Computation, Elsevier, vol. 478(C).
    19. Xie, Lifei & Cheng, Jun & Wang, Hailing & Wang, Jiange & Hu, Mengjie & Zhou, Zhidong, 2022. "Memory-based event-triggered asynchronous control for semi-Markov switching systems," Applied Mathematics and Computation, Elsevier, vol. 415(C).
    20. Xue, Yu & Tu, Kairong & Liu, Chunyan & Zhang, Xian, 2024. "Non-fragile extended dissipative synchronization control for uncertain discrete-time neural networks with leakage and unbounded time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 185(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:eee:apmaco:v:477:y:2024:i:c:s0096300324002613. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.