IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v484y2025ics0096300324004557.html
   My bibliography  Save this article

Reachable set estimation of delayed second-order memristive neural networks

Author

Listed:
  • Shen, Yi
  • Zhao, Jiemei
  • Yu, Liqi

Abstract

This study is concerned with reachable set bounding of delayed second-order memristive neural networks (SMNNs) with bounded input disturbances. By applying an analytic method, some inequality techniques and an adaptive control strategy, a sufficient condition of reachable set estimation criterion is derived to guarantee that the states of delayed SMNNs are bounded by a compact ellipsoid. A non-reduced order method is employed to investigate the reachable set bounding problem instead of the reduced order method by variable substitution. In addition, the proposed result is presented in algebraic form, which is easy to test. Finally, a simulation is performed to demonstrate the validity of the proposed algorithm.

Suggested Citation

  • Shen, Yi & Zhao, Jiemei & Yu, Liqi, 2025. "Reachable set estimation of delayed second-order memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 484(C).
    • Handle: RePEc:eee:apmaco:v:484:y:2025:i:c:s0096300324004557
    DOI: 10.1016/j.amc.2024.128994
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300324004557
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2024.128994?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. C. Durieu & É. Walter & B. Polyak, 2001. "Multi-Input Multi-Output Ellipsoidal State Bounding," Journal of Optimization Theory and Applications, Springer, vol. 111(2), pages 273-303, November.
    2. Liu, Guobao & Chen, Xiangyong & Shen, Zhongyu & Liu, Yajuan & Jia, Xianglei, 2022. "Reachable set estimation for continuous delayed singularly perturbed systems with bounded disturbances," Applied Mathematics and Computation, Elsevier, vol. 416(C).
    3. Dong, Shiyu & Zhu, Hong & Zhong, Shouming & Shi, Kaibo & Liu, Yajuan, 2021. "New study on fixed-time synchronization control of delayed inertial memristive neural networks," Applied Mathematics and Computation, Elsevier, vol. 399(C).
    4. Zhou, Chao & Wang, Chunhua & Yao, Wei & Lin, Hairong, 2022. "Observer-based synchronization of memristive neural networks under DoS attacks and actuator saturation and its application to image encryption," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    5. Zhao, Mingfang & Li, Hong-Li & Zhang, Long & Hu, Cheng & Jiang, Haijun, 2023. "Quasi-synchronization of discrete-time fractional-order quaternion-valued memristive neural networks with time delays and uncertain parameters," Applied Mathematics and Computation, Elsevier, vol. 453(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. Zhao, Ningning & Qiao, Yuanhua, 2024. "Stability analysis of Clifford-valued memristor-based neural networks with impulsive disturbances and its application to image encryption," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    2. Jiang, Tingting & Zhang, Yuping & Zeng, Yong & Zhong, Shouming & Shi, Kaibo & Cai, Xiao, 2021. "Finite-time analysis for networked predictive control systems with induced time delays and data packet dropouts," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    3. Guo, Fang & Luo, Mengzhuo & Cheng, Jun & Katib, Iyad & Shi, Kaibo, 2023. "Nonfragile observer-based event-triggered fuzzy tracking control for fast-sampling singularly perturbed systems with dual-layer switching mechanism and cyber-attacks," Chaos, Solitons & Fractals, Elsevier, vol. 175(P1).
    4. 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).
    5. Fan, Yi & Wang, Pengjun & Heidari, Ali Asghar & Chen, Huiling & HamzaTurabieh, & Mafarja, Majdi, 2022. "Random reselection particle swarm optimization for optimal design of solar photovoltaic modules," Energy, Elsevier, vol. 239(PA).
    6. 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.
    7. Yongchun Jiang & Hongli Yang & Ivan Ganchev Ivanov, 2024. "Reachable Set Estimation and Controller Design for Linear Time-Delayed Control System with Disturbances," Mathematics, MDPI, vol. 12(2), pages 1-10, January.
    8. 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).
    9. 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).
    10. Fei Yu & Wuxiong Zhang & Xiaoli Xiao & Wei Yao & Shuo Cai & Jin Zhang & Chunhua Wang & Yi Li, 2023. "Dynamic Analysis and FPGA Implementation of a New, Simple 5D Memristive Hyperchaotic Sprott-C System," Mathematics, MDPI, vol. 11(3), pages 1-15, January.
    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. Huang, Zhuoyuan & Bao, Haibo, 2024. "Output synchronization of reaction-diffusion neural networks with multiple output couplings via generalized intermittent control," Applied Mathematics and Computation, Elsevier, vol. 477(C).
    13. Qifeng Fu & Xuemei Xu & Chuwen Xiao, 2022. "LQR Chaos Synchronization for a Novel Memristor-Based Hyperchaotic Oscillator," Mathematics, MDPI, vol. 11(1), pages 1-16, December.
    14. Amirreza Fahim Golestaneh, 2022. "A Closed-Form Parametrization and an Alternative Computational Algorithm for Approximating Slices of Minkowski Sums of Ellipsoids in R 3," Mathematics, MDPI, vol. 11(1), pages 1-21, December.
    15. Alsaedi, Ahmed & Cao, Jinde & Ahmad, Bashir & Alshehri, Ahmed & Tan, Xuegang, 2022. "Synchronization of master-slave memristive neural networks via fuzzy output-based adaptive strategy," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    16. Liao, Wei & Liang, Taotao & Wei, Xiaohui & Yin, Qiaozhi, 2022. "Probabilistic reach-Avoid problems in nondeterministic systems with time-Varying targets and obstacles," Applied Mathematics and Computation, Elsevier, vol. 425(C).
    17. 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).
    18. Liao, Wei & Liang, Taotao & Wang, Chen & Yang, Dayong, 2023. "A dimensionality reduction method for computing reachable tubes based on piecewise pseudo-time dependent Hamilton–Jacobi equation," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    19. Zhang, Liang & Feng, Zhiguang & Jiang, Zhengyi & Zhao, Ning & Yang, Yang, 2020. "Improved results on reachable set estimation of singular systems," Applied Mathematics and Computation, Elsevier, vol. 385(C).
    20. Liu, Yun & Heidari, Ali Asghar & Ye, Xiaojia & Liang, Guoxi & Chen, Huiling & He, Caitou, 2021. "Boosting slime mould algorithm for parameter identification of photovoltaic models," Energy, Elsevier, vol. 234(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:484:y:2025:i:c:s0096300324004557. 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.