IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v265y2015icp333-346.html
   My bibliography  Save this article

Global asymptotic stability of nonautonomous Cohen–Grossberg neural network models with infinite delays

Author

Listed:
  • Esteves, Salete
  • Oliveira, José J.

Abstract

For a general Cohen–Grossberg neural network model with potentially unbounded time-varying coefficients and infinite distributed delays, we give sufficient conditions for its global asymptotic stability. The model studied is general enough to include, as subclass, the most of famous neural network models such as Cohen–Grossberg, Hopfield, and bidirectional associative memory. Contrary to usual in the literature, in the proofs we do not use Lyapunov functionals. As illustrated, the results are applied to several concrete models studied in the literature and a comparison of results shows that our results give new global stability criteria for several neural network models and improve some earlier publications.

Suggested Citation

  • Esteves, Salete & Oliveira, José J., 2015. "Global asymptotic stability of nonautonomous Cohen–Grossberg neural network models with infinite delays," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 333-346.
  • Handle: RePEc:eee:apmaco:v:265:y:2015:i:c:p:333-346
    DOI: 10.1016/j.amc.2015.04.103
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300315005652
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2015.04.103?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. Jiang, Haijun & Teng, Zhidong, 2006. "Boundedness and global stability for nonautonomous recurrent neural networks with distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 30(1), pages 83-93.
    2. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2009. "Global exponential stability for nonautonomous cellular neural networks with unbounded delays," Chaos, Solitons & Fractals, Elsevier, vol. 39(3), pages 1144-1151.
    3. Zhang, Qiang & Wei, Xiaopeng & Xu, Jin, 2009. "Exponential stability for nonautonomous neural networks with variable delays," Chaos, Solitons & Fractals, Elsevier, vol. 39(3), pages 1152-1157.
    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. Yuan, Jun & Zhao, Lingzhi & Huang, Chengdai & Xiao, Min, 2019. "Novel results on bifurcation for a fractional-order complex-valued neural network with leakage delay," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 868-883.
    2. Huang, Chengdai & Cao, Jinde & Xiao, Min & Alsaedi, Ahmed & Hayat, Tasawar, 2017. "Bifurcations in a delayed fractional complex-valued neural network," Applied Mathematics and Computation, Elsevier, vol. 292(C), pages 210-227.
    3. Zhang, Chuan-Ke & He, Yong & Jiang, Lin & Lin, Wen-Juan & Wu, Min, 2017. "Delay-dependent stability analysis of neural networks with time-varying delay: A generalized free-weighting-matrix approach," Applied Mathematics and Computation, Elsevier, vol. 294(C), pages 102-120.
    4. Balasundaram, K. & Raja, R. & Pratap, A. & Chandrasekaran, S., 2019. "Impulsive effects on competitive neural networks with mixed delays: Existence and exponential stability analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 290-302.

    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. Dehao Ruan & Yao Lu, 2024. "Generalized Halanay Inequalities and Asymptotic Behavior of Nonautonomous Neural Networks with Infinite Delays," Mathematics, MDPI, vol. 12(1), pages 1-19, January.
    2. Rakkiyappan, R. & Balasubramaniam, P., 2009. "LMI conditions for stability of stochastic recurrent neural networks with distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 1688-1696.
    3. Song, Qiankun & Wang, Zidong, 2008. "Neural networks with discrete and distributed time-varying delays: A general stability analysis," Chaos, Solitons & Fractals, Elsevier, vol. 37(5), pages 1538-1547.
    4. Wang, Xin & Zhuang, Guangming & Chen, Guoliang & Ma, Qian & Lu, Junwei, 2022. "Asynchronous mixed H∞ and passive control for fuzzy singular delayed Markovian jump system via hidden Markovian model mechanism," Applied Mathematics and Computation, Elsevier, vol. 429(C).
    5. Ye, Zhiyong & Zhang, He & Zhang, Hongyu & Zhang, Hua & Lu, Guichen, 2015. "Mean square stabilization and mean square exponential stabilization of stochastic BAM neural networks with Markovian jumping parameters," Chaos, Solitons & Fractals, Elsevier, vol. 73(C), pages 156-165.
    6. Qian-hong Zhang & Li-hui Yang, 2012. "Dynamical analysis of fuzzy BAM neural networks with variable delays," Fuzzy Information and Engineering, Springer, vol. 4(1), pages 93-104, March.
    7. Cai, Liming & Li, Xuezhi & Yu, Jingyuan & Zhu, Guangtian, 2009. "Dynamics of a nonautonomous predator–prey dispersion–delay system with Beddington–DeAngelis functional response," Chaos, Solitons & Fractals, Elsevier, vol. 40(4), pages 2064-2075.
    8. Wang, Mei-Qi & Ma, Wen-Li & Li, Yuan & Chen, En-Li & Liu, Peng-Fei & Zhang, Ming-Zhi, 2022. "Dynamic analysis of piecewise nonlinear systems with fractional differential delay feedback control," Chaos, Solitons & Fractals, Elsevier, vol. 164(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:265:y:2015:i:c:p:333-346. 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.