IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v174y2023ics0960077923006732.html
   My bibliography  Save this article

Complete synchronization for discrete-time fractional-order coupled neural networks with time delays

Author

Listed:
  • Cui, Xueke
  • Li, Hong-Li
  • Zhang, Long
  • Hu, Cheng
  • Bao, Haibo

Abstract

This paper is devoted to investigating complete synchronization for a class of discrete-time fractional-order coupled neural networks (DFCNNs) with time delays, which has not been documented yet. For the sake of answering the challenging problem mentioned above, we generalize the classic Barbalat’s lemma to discrete-time fractional-order (DF) version. After that a novel hybrid controller composed of adaptive control term and delayed feedback control term is firstly designed to reach synchronization of DFCNNs with time delays. Then, several well-done synchronization criteria are acquired by the utilization of fractional calculus theory, DF Barbalat’s lemma and inequality techniques. In the end, a numerical example is put forward to exemplify the validity of our results.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:chsofr:v:174:y:2023:i:c:s0960077923006732
    DOI: 10.1016/j.chaos.2023.113772
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923006732
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2023.113772?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. Zhang, Xiao-Li & Li, Hong-Li & Kao, Yonggui & Zhang, Long & Jiang, Haijun, 2022. "Global Mittag-Leffler synchronization of discrete-time fractional-order neural networks with time delays," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    2. 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).
    3. Hu, Jingting & Sui, Guixia & Li, Xiaodi, 2020. "Fixed-time synchronization of complex networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    4. 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).
    5. Thabet Abdeljawad, 2013. "On Delta and Nabla Caputo Fractional Differences and Dual Identities," Discrete Dynamics in Nature and Society, Hindawi, vol. 2013, pages 1-12, July.
    6. 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).
    7. Thabet Abdeljawad & Ferhan M. Atici, 2012. "On the Definitions of Nabla Fractional Operators," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-13, October.
    8. Shi, Lin & Zhang, Chunmei & Zhong, Shouming, 2021. "Synchronization of singular complex networks with time-varying delay via pinning control and linear feedback control," Chaos, Solitons & Fractals, Elsevier, vol. 145(C).
    9. Cao, Jinde & Wang, Zidong & Sun, Yonghui, 2007. "Synchronization in an array of linearly stochastically coupled networks with time delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(2), pages 718-728.
    10. Feng, Liang & Hu, Cheng & Yu, Juan & Jiang, Haijun & Wen, Shiping, 2021. "Fixed-time Synchronization of Coupled Memristive Complex-valued Neural Networks," Chaos, Solitons & Fractals, Elsevier, vol. 148(C).
    11. Gu, Yajuan & Wang, Hu & Yu, Yongguang, 2020. "Synchronization for fractional-order discrete-time neural networks with time delays," Applied Mathematics and Computation, Elsevier, vol. 372(C).
    12. Zheng, Bibo & Wang, Zhanshan, 2022. "Mittag-Leffler synchronization of fractional-order coupled neural networks with mixed delays," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    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. Stamov, Trayan, 2024. "Practical stability criteria for discrete fractional neural networks in product form design analysis," Chaos, Solitons & Fractals, Elsevier, vol. 179(C).
    2. Li, Rui & Xu, Bang-Lin & Chen, De-Bao & Zhou, Jian-Fang & Yuan, Wu-Jie, 2023. "Transitions to synchronization induced by synaptic increasing in coupled tonic neurons with electrical synapses," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    3. Sun, Wenjing & Tang, Ze & Feng, Jianwen & Park, Ju H., 2024. "Quasi-synchronization of heterogeneous neural networks with hybrid time delays via sampled-data saturating impulsive control," Chaos, Solitons & Fractals, Elsevier, vol. 182(C).

    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. 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.
    2. Zhang, Xiao-Li & Li, Hong-Li & Kao, Yonggui & Zhang, Long & Jiang, Haijun, 2022. "Global Mittag-Leffler synchronization of discrete-time fractional-order neural networks with time delays," Applied Mathematics and Computation, Elsevier, vol. 433(C).
    3. Li, Ruoxia & Cao, Jinde & Xue, Changfeng & Manivannan, R., 2021. "Quasi-stability and quasi-synchronization control of quaternion-valued fractional-order discrete-time memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 395(C).
    4. 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).
    5. Jiraporn Reunsumrit & Thanin Sitthiwirattham, 2020. "On the Nonlocal Fractional Delta-Nabla Sum Boundary Value Problem for Sequential Fractional Delta-Nabla Sum-Difference Equations," Mathematics, MDPI, vol. 8(4), pages 1-13, March.
    6. 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).
    7. Rashid, Saima & Sultana, Sobia & Hammouch, Zakia & Jarad, Fahd & Hamed, Y.S., 2021. "Novel aspects of discrete dynamical type inequalities within fractional operators having generalized ℏ-discrete Mittag-Leffler kernels and application," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    8. Suwan, Iyad & Abdeljawad, Thabet & Jarad, Fahd, 2018. "Monotonicity analysis for nabla h-discrete fractional Atangana–Baleanu differences," Chaos, Solitons & Fractals, Elsevier, vol. 117(C), pages 50-59.
    9. Qiushuang Wang & Run Xu, 2022. "On Hilfer Generalized Proportional Nabla Fractional Difference Operators," Mathematics, MDPI, vol. 10(15), pages 1-16, July.
    10. Pshtiwan Othman Mohammed & Thabet Abdeljawad & Faraidun Kadir Hamasalh, 2021. "On Riemann—Liouville and Caputo Fractional Forward Difference Monotonicity Analysis," Mathematics, MDPI, vol. 9(11), pages 1-17, June.
    11. Rashid, Saima & Sultana, Sobia & Jarad, Fahd & Jafari, Hossein & Hamed, Y.S., 2021. "More efficient estimates via ℏ-discrete fractional calculus theory and applications," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    12. Lu Pang & Cheng Hu & Juan Yu & Haijun Jiang, 2022. "Fixed-Time Synchronization for Fuzzy-Based Impulsive Complex Networks," Mathematics, MDPI, vol. 10(9), pages 1-16, May.
    13. Arinushkin, P.A. & Vadivasova, T.E., 2021. "Nonlinear damping effects in a simplified power grid model based on coupled Kuramoto-like oscillators with inertia," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
    14. Li, Xinna & Wu, Huaiqin & Cao, Jinde, 2023. "Prescribed-time synchronization in networks of piecewise smooth systems via a nonlinear dynamic event-triggered control strategy," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 647-668.
    15. 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).
    16. Mairemunisa Abudusaimaiti & Abuduwali Abudukeremu & Amina Sabir, 2023. "Fixed/Preassigned-Time Stochastic Synchronization of Complex-Valued Fuzzy Neural Networks with Time Delay," Mathematics, MDPI, vol. 11(17), pages 1-18, September.
    17. Enli Wu & Yao Wang & Yundong Li & Kelin Li & Fei Luo, 2023. "Fixed-Time Synchronization of Complex-Valued Coupled Networks with Hybrid Perturbations via Quantized Control," Mathematics, MDPI, vol. 11(18), pages 1-18, September.
    18. Yifan Zhang & Tianzeng Li & Zhiming Zhang & Yu Wang, 2022. "Novel Methods for the Global Synchronization of the Complex Dynamical Networks with Fractional-Order Chaotic Nodes," Mathematics, MDPI, vol. 10(11), pages 1-22, June.
    19. Tseng, Jui-Pin, 2016. "A novel approach to synchronization of nonlinearly coupled network systems with delays," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 452(C), pages 266-280.
    20. Abdurahman, Abdujelil & Abudusaimaiti, Mairemunisa & Jiang, Haijun, 2023. "Fixed/predefined-time lag synchronization of complex-valued BAM neural networks with stochastic perturbations," Applied Mathematics and Computation, Elsevier, vol. 444(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:174:y:2023:i:c:s0960077923006732. 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.