IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v178y2024ics0960077923012390.html
   My bibliography  Save this article

Successive lag synchronization of heterogeneous distributed-order coupled neural networks with unbounded delayed coupling

Author

Listed:
  • Yang, Dongsheng
  • Yu, Yongguang
  • Wang, Hu
  • Ren, Guojian
  • Zhang, Xiaoli

Abstract

The problem of successive lag synchronization (SLS) for heterogeneous distributed-order coupled neural networks (HDOCNNs) with unbounded delayed coupling is investigated in this paper. Firstly, a model for HDOCNNs under the framework of distributed order Caputo derivative is proposed which is the generalization of integer order and fractional order cases. Secondly, a new Razumikhin-type stability theorem for distributed order systems is proposed. On this basis, the well-known Halanay type inequality is generalized to analyze the convergence of solutions for a class of distributed order dynamical systems. Thirdly, the SLS criteria for HDOCNNs with delayed coupling by designing a novel adaptive controller and a valid feedback controller are presented herein, respectively. Finally, a numerical example is presented to illustrate the reliability of the proposed scheme.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012390
    DOI: 10.1016/j.chaos.2023.114337
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923012390
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.114337?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. 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).
    2. Xu, Shaochuan & Wang, Xingyuan & Ye, Xiaolin, 2022. "A new fractional-order chaos system of Hopfield neural network and its application in image encryption," Chaos, Solitons & Fractals, Elsevier, vol. 157(C).
    3. Chen, Yuan & Wu, Jianwei & Bao, Haibo, 2022. "Finite-time stabilization for delayed quaternion-valued coupled neural networks with saturated impulse," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    4. 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).
    5. Mo, Wenjun & Bao, Haibo, 2022. "Finite-time synchronization for fractional-order quaternion-valued coupled neural networks with saturated impulse," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    6. Shafiya, M. & Nagamani, G., 2022. "New finite-time passivity criteria for delayed fractional-order neural networks based on Lyapunov function approach," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    7. Zhang, Meihui & Jia, Jinhong & Zheng, Xiangcheng, 2023. "Numerical approximation and fast implementation to a generalized distributed-order time-fractional option pricing model," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    8. 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).
    9. Kumar, Yashveer & Yadav, Poonam & Singh, Vineet Kumar, 2023. "Distributed order Gauss-Quadrature scheme for distributed order fractional sub-diffusion model," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    10. Babu, N. Ramesh & Balasubramaniam, P., 2022. "Master-slave synchronization of a new fractal-fractional order quaternion-valued neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
    11. Pourbabaee, Marzieh & Saadatmandi, Abbas, 2019. "A novel Legendre operational matrix for distributed order fractional differential equations," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 215-231.
    12. Aadhithiyan, S. & Raja, R. & Zhu, Q. & Alzabut, J. & Niezabitowski, M. & Lim, C.P., 2021. "Modified projective synchronization of distributive fractional order complex dynamic networks with model uncertainty via adaptive control," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    13. Mahmoud, Gamal M. & Aboelenen, Tarek & Abed-Elhameed, Tarek M. & Farghaly, Ahmed A., 2021. "On boundedness and projective synchronization of distributed order neural networks," Applied Mathematics and Computation, Elsevier, vol. 404(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. 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.
    2. Cui, Xueke & Li, Hong-Li & Zhang, Long & Hu, Cheng & Bao, Haibo, 2023. "Complete synchronization for discrete-time fractional-order coupled neural networks with time delays," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    3. Jibin Yang & Xiaohui Xu & Quan Xu & Haolin Yang & Mengge Yu, 2024. "Stability and Synchronization of Delayed Quaternion-Valued Neural Networks under Multi-Disturbances," Mathematics, MDPI, vol. 12(6), pages 1-26, March.
    4. 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.
    5. Shi, Jinyao & Zhou, Peipei & Cai, Shuiming & Jia, Qiang, 2023. "Exponential synchronization for multi-weighted dynamic networks via finite-level quantized control with adaptive scaling gain," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    6. Li, Peiluan & Gao, Rong & Xu, Changjin & Ahmad, Shabir & Li, Ying & Akgül, Ali, 2023. "Bifurcation behavior and PDγ control mechanism of a fractional delayed genetic regulatory model," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    7. Hairong Lin & Chunhua Wang & Fei Yu & Jingru Sun & Sichun Du & Zekun Deng & Quanli Deng, 2023. "A Review of Chaotic Systems Based on Memristive Hopfield Neural Networks," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
    8. Kumar, Yashveer & Singh, Vineet Kumar, 2021. "Computational approach based on wavelets for financial mathematical model governed by distributed order fractional differential equation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 190(C), pages 531-569.
    9. S M, Sivalingam & Kumar, Pushpendra & Govindaraj, V., 2023. "A novel numerical scheme for fractional differential equations using extreme learning machine," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    10. He, Jin-Man & Pei, Li-Jun, 2023. "Function matrix projection synchronization for the multi-time delayed fractional order memristor-based neural networks with parameter uncertainty," Applied Mathematics and Computation, Elsevier, vol. 454(C).
    11. Marasi, H.R. & Derakhshan, M.H. & Ghuraibawi, Amer A. & Kumar, Pushpendra, 2024. "A novel method based on fractional order Gegenbauer wavelet operational matrix for the solutions of the multi-term time-fractional telegraph equation of distributed order," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 217(C), pages 405-424.
    12. Vikneswari Someetheram & Muhammad Fadhil Marsani & Mohd Shareduwan Mohd Kasihmuddin & Nur Ezlin Zamri & Siti Syatirah Muhammad Sidik & Siti Zulaikha Mohd Jamaludin & Mohd. Asyraf Mansor, 2022. "Random Maximum 2 Satisfiability Logic in Discrete Hopfield Neural Network Incorporating Improved Election Algorithm," Mathematics, MDPI, vol. 10(24), pages 1-29, December.
    13. Oliveira, José J., 2022. "Global stability criteria for nonlinear differential systems with infinite delay and applications to BAM neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).
    14. Jayaraman Venkatesh & Alexander N. Pchelintsev & Anitha Karthikeyan & Fatemeh Parastesh & Sajad Jafari, 2023. "A Fractional-Order Memristive Two-Neuron-Based Hopfield Neuron Network: Dynamical Analysis and Application for Image Encryption," Mathematics, MDPI, vol. 11(21), pages 1-17, October.
    15. Amine, Saida & Hajri, Youssra & Allali, Karam, 2022. "A delayed fractional-order tumor virotherapy model: Stability and Hopf bifurcation," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    16. Shafiya, M. & Nagamani, G., 2022. "New finite-time passivity criteria for delayed fractional-order neural networks based on Lyapunov function approach," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    17. Pourbabaee, Marzieh & Saadatmandi, Abbas, 2022. "A new operational matrix based on Müntz–Legendre polynomials for solving distributed order fractional differential equations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 210-235.
    18. Kiruthika, R. & Krishnasamy, R. & Lakshmanan, S. & Prakash, M. & Manivannan, A., 2023. "Non-fragile sampled-data control for synchronization of chaotic fractional-order delayed neural networks via LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 169(C).
    19. 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).
    20. 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).

    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:chsofr:v:178:y:2024:i:c:s0960077923012390. 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: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    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.