IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v182y2021icp858-870.html
   My bibliography  Save this article

Prescribed convergence analysis of recurrent neural networks with parameter variations

Author

Listed:
  • Bao, Gang
  • Zeng, Zhigang

Abstract

Recurrent neural networks are designed to be convergent to the desired equilibrium point for their applications. Network parameter variations lead network states to other different points. So this paper discusses the prescribed convergence problem of recurrent neural networks with parameter variations. Firstly, we recurrent neural networks’ equilibrium point variation principles when parameters are changed. Then we design one track controller to make recurrent neural networks be convergent to the prescribed equilibrium for known parameter variations. Next, we present one adaptive controller to lead network states to the desired equilibrium for unknown parameter variations. At last, two examples are given for validating the presented methods.

Suggested Citation

  • Bao, Gang & Zeng, Zhigang, 2021. "Prescribed convergence analysis of recurrent neural networks with parameter variations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 858-870.
    • Handle: RePEc:eee:matcom:v:182:y:2021:i:c:p:858-870
    DOI: 10.1016/j.matcom.2020.12.010
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475420304651
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2020.12.010?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. Gao, Ming & Cui, Baotong, 2009. "Robust exponential stability of interval Cohen–Grossberg neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1914-1928.
    2. Li, Xiaoqing & She, Kun & Zhong, Shouming & Shi, Kaibo & Kang, Wei & Cheng, Jun & Yu, Yongbin, 2018. "Extended robust global exponential stability for uncertain switched memristor-based neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 325(C), pages 271-290.
    3. Cui, Shihua & Zhao, Tao & Guo, Jie, 2009. "Global robust exponential stability for interval neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1567-1576.
    4. Wenguang Luo & Xiuling Wang & Yonghua Liu & Hongli Lan, 2013. "Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-7, February.
    5. Tang, Qian & Jian, Jigui, 2019. "Global exponential convergence for impulsive inertial complex-valued neural networks with time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 159(C), pages 39-56.
    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. Lan, Heng-you & Cui, Yi-Shun, 2009. "A neural network method for solving a system of linear variational inequalities," Chaos, Solitons & Fractals, Elsevier, vol. 41(3), pages 1245-1252.
    2. 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.
    3. 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).
    4. Li, Xiaoqing & Nguang, Sing Kiong & She, Kun & Cheng, Jun & Zhong, Shouming, 2021. "Resilient controller synthesis for Markovian jump systems with probabilistic faults and gain fluctuations under stochastic sampling operational mechanism," Applied Mathematics and Computation, Elsevier, vol. 392(C).
    5. Han, Siyu & Hu, Cheng & Yu, Juan & Jiang, Haijun & Wen, Shiping, 2021. "Stabilization of inertial Cohen-Grossberg neural networks with generalized delays: A direct analysis approach," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    6. Sheng, Li & Yang, Huizhong, 2009. "Robust stability of uncertain Markovian jumping Cohen–Grossberg neural networks with mixed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2120-2128.
    7. Pan, Jinsong & Zhang, Zhengqiu, 2021. "Finite-time synchronization for delayed complex-valued neural networks via the exponential-type controllers of time variable," Chaos, Solitons & Fractals, Elsevier, vol. 146(C).
    8. Kumar, Ankit & Das, Subir & Singh, Sunny & Rajeev,, 2023. "Quasi-projective synchronization of inertial complex-valued recurrent neural networks with mixed time-varying delay and mismatched parameters," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    9. Iswarya, M. & Raja, R. & Cao, J. & Niezabitowski, M. & Alzabut, J. & Maharajan, C., 2022. "New results on exponential input-to-state stability analysis of memristor based complex-valued inertial neural networks with proportional and distributed delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 440-461.
    10. Wei, Xiaofeng & Zhang, Ziye & Lin, Chong & Chen, Jian, 2021. "Synchronization and anti-synchronization for complex-valued inertial neural networks with time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 403(C).
    11. 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.
    12. Jian, Jigui & Wu, Kai & Wang, Baoxian, 2020. "Global Mittag-Leffler boundedness and synchronization for fractional-order chaotic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    13. Zhao, Rui & Wang, Baoxian & Jian, Jigui, 2022. "Global μ-stabilization of quaternion-valued inertial BAM neural networks with time-varying delays via time-delayed impulsive control," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 202(C), pages 223-245.
    14. Lin, Dongyuan & Chen, Xiaofeng & Yu, Guoping & Li, Zhongshan & Xia, Yannan, 2021. "Global exponential synchronization via nonlinear feedback control for delayed inertial memristor-based quaternion-valued neural networks with impulses," Applied Mathematics and Computation, Elsevier, vol. 401(C).
    15. Wang, Shengbo & Cao, Yanyi & Huang, Tingwen & Wen, Shiping, 2019. "Passivity and passification of memristive neural networks with leakage term and time-varying delays," Applied Mathematics and Computation, Elsevier, vol. 361(C), pages 294-310.

    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:182:y:2021:i:c:p:858-870. 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.