IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v212y2023icp49-65.html
   My bibliography  Save this article

Adaptive quasi-synchronization analysis for Caputo delayed Cohen–Grossberg neural networks

Author

Listed:
  • Zhang, Hai
  • Chen, Xinbin
  • Ye, Renyu
  • Stamova, Ivanka
  • Cao, Jinde

Abstract

The quasi-synchronization (QS) issues for Caputo delayed Cohen–Grossberg neural networks (CGNNs) are discussed in this article. To begin with, a novel lemma is established by constructing suitable fractional differential inequality. Due to the advantages of adaptive control schemes with reducing control cost and having high tracking accuracy, two different adaptive controllers are designed, respectively. Applying the proposed lemma, inequality techniques and Lagrange’s mean value theorem, the conditions of QS are obtained by selecting appropriate Lyapunov functions. Finally, two numerical examples in different dimensions are shown to test the correctness of the gained theorems.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:matcom:v:212:y:2023:i:c:p:49-65
    DOI: 10.1016/j.matcom.2023.04.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475423001805
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2023.04.025?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. 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 & Cheng, Yuhong & Zhang, Weiwei & Zhang, Hongmei, 2023. "Time-dependent and Caputo derivative order-dependent quasi-uniform synchronization on fuzzy neural networks with proportional and distributed delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 846-857.
    3. Xu, Changjin & Liao, Maoxin & Li, Peiluan & Yuan, Shuai, 2021. "Impact of leakage delay on bifurcation in fractional-order complex-valued neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    4. Tan, Hailian & Wu, Jianwei & Bao, Haibo, 2022. "Event-triggered impulsive synchronization of fractional-order coupled neural networks," Applied Mathematics and Computation, Elsevier, vol. 429(C).
    5. Hu, Taotao & He, Zheng & Zhang, Xiaojun & Zhong, Shouming, 2020. "Finite-time stability for fractional-order complex-valued neural networks with time delay," Applied Mathematics and Computation, Elsevier, vol. 365(C).
    6. Uribarri, Gonzalo & Mindlin, Gabriel B., 2022. "Dynamical time series embeddings in recurrent neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 154(C).
    7. Stamova, Ivanka & Stamov, Trayan & Stamov, Gani, 2022. "Lipschitz stability analysis of fractional-order impulsive delayed reaction-diffusion neural network models," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    8. 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.
    9. 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).
    10. Chen, Wei & Yu, Yongguang & Hai, Xudong & Ren, Guojian, 2022. "Adaptive quasi-synchronization control of heterogeneous fractional-order coupled neural networks with reaction-diffusion," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    11. Li, Donghua & Zhang, Zhengqiu & Zhang, Xiaoluan, 2020. "Periodic solutions of discrete-time Quaternion-valued BAM neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    12. Yan, Hongyun & Qiao, Yuanhua & Duan, Lijuan & Miao, Jun, 2022. "New results of quasi-projective synchronization for fractional-order complex-valued neural networks with leakage and discrete delays," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    13. Hu, Binxin & Song, Qiankun & Zhao, Zhenjiang, 2020. "Robust state estimation for fractional-order complex-valued delayed neural networks with interval parameter uncertainties: LMI approach," Applied Mathematics and Computation, Elsevier, vol. 373(C).
    14. Zhang, Hai & Cheng, Yuhong & Zhang, Hongmei & Zhang, Weiwei & Cao, Jinde, 2022. "Hybrid control design for Mittag-Leffler projective synchronization on FOQVNNs with multiple mixed delays and impulsive effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 197(C), pages 341-357.
    15. Sun, Lin & Su, Lei & Wang, Jing, 2021. "Non-fragile dissipative state estimation for semi-Markov jump inertial neural networks with reaction-diffusion," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    16. Xu, Liguang & Chu, Xiaoyan & Hu, Hongxiao, 2021. "Quasi-synchronization analysis for fractional-order delayed complex dynamical networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 594-613.
    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. Wang, Chen & Zhang, Hai & Ye, Renyu & Zhang, Weiwei & Zhang, Hongmei, 2023. "Finite time passivity analysis for Caputo fractional BAM reaction–diffusion delayed neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 208(C), pages 424-443.
    2. Li, Xuemei & Liu, Xinge & Wang, Fengxian, 2023. "Anti-synchronization of fractional-order complex-valued neural networks with a leakage delay and time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    3. Udhayakumar, K. & Rakkiyappan, R. & Li, Xiaodi & Cao, Jinde, 2021. "Mutiple ψ-type stability of fractional-order quaternion-valued neural networks," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    4. Luo, Lingao & Li, Lulu & Huang, Wei, 2024. "Asymptotic stability of fractional-order Hopfield neural networks with event-triggered delayed impulses and switching effects," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 219(C), pages 491-504.
    5. Deng, Jie & Li, Hong-Li & Cao, Jinde & Hu, Cheng & Jiang, Haijun, 2023. "State estimation for discrete-time fractional-order neural networks with time-varying delays and uncertainties," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    6. Yang, Dongsheng & Yu, Yongguang & Wang, Hu & Ren, Guojian & Zhang, Xiaoli, 2024. "Successive lag synchronization of heterogeneous distributed-order coupled neural networks with unbounded delayed coupling," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    7. Yaning Yu & Ziye Zhang, 2022. "State Estimation for Complex-Valued Inertial Neural Networks with Multiple Time Delays," Mathematics, MDPI, vol. 10(10), pages 1-14, May.
    8. Xu, Changjin & Liu, Zixin & Yao, Lingyun & Aouiti, Chaouki, 2021. "Further exploration on bifurcation of fractional-order six-neuron bi-directional associative memory neural networks with multi-delays," Applied Mathematics and Computation, Elsevier, vol. 410(C).
    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. Sun, Yuting & Hu, Cheng & Yu, Juan & Shi, Tingting, 2023. "Synchronization of fractional-order reaction-diffusion neural networks via mixed boundary control," Applied Mathematics and Computation, Elsevier, vol. 450(C).
    11. Gao, Panqing & Ye, Renyu & Zhang, Hai & Stamova, Ivanka & Cao, Jinde, 2024. "Asymptotic stability and quantitative synchronization of fractional competitive neural networks with multiple restrictions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 338-353.
    12. Peng, Qiu & Jian, Jigui, 2023. "Synchronization analysis of fractional-order inertial-type neural networks with time delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 62-77.
    13. 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.
    14. Zhang, Zhengqiu & Yang, Zhen, 2023. "Asymptotic stability for quaternion-valued fuzzy BAM neural networks via integral inequality approach," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    15. Fu, Xiuwen & Sheng, Zhaoliang & Lin, Chong & Chen, Bing, 2022. "New results on admissibility and dissipativity analysis of descriptor time-delay systems," Applied Mathematics and Computation, Elsevier, vol. 419(C).
    16. Gao, Shang & Peng, Keyu & Zhang, Chunrui, 2021. "Existence and global exponential stability of periodic solutions for feedback control complex dynamical networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    17. Li, Mingyue & Chen, Huanzhen & Li, Xiaodi, 2021. "Exponential stability of nonlinear systems involving partial unmeasurable states via impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    18. Tan, Lihua & Li, Chuandong & Huang, Junjian & Huang, Tingwen, 2021. "Output feedback leader-following consensus for nonlinear stochastic multiagent systems: The event-triggered method," Applied Mathematics and Computation, Elsevier, vol. 395(C).
    19. Gani Stamov & Ivanka Stamova & George Venkov & Trayan Stamov & Cvetelina Spirova, 2020. "Global Stability of Integral Manifolds for Reaction–Diffusion Delayed Neural Networks of Cohen–Grossberg-Type under Variable Impulsive Perturbations," Mathematics, MDPI, vol. 8(7), pages 1-18, July.
    20. Guo, Ying & Li, Yuze, 2022. "Bipartite leader-following synchronization of fractional-order delayed multilayer signed networks by adaptive and impulsive controllers," Applied Mathematics and Computation, Elsevier, vol. 430(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:matcom:v:212:y:2023:i:c:p:49-65. 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/mathematics-and-computers-in-simulation/ .

    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.