IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v40y2009i2p697-707.html
   My bibliography  Save this article

Stability analysis of neural networks with both variable and unbounded delays

Author

Listed:
  • Zhao, Weirui
  • Yan, Anzhi

Abstract

In this paper, the stability of neural networks with both variable and unbounded delays is investigated. With simpler assumption that the activation functions are continuous and monotone non-decreasing, we employ homeomorphism techniques and Lyapunov functional to establish some sufficient conditions ensuring the global asymptotic stability and exponential stability of equilibrium of neural networks with both variable and unbounded delays. The new and useful results obtained in this paper extend and improve the existing ones in the previous literature.

Suggested Citation

  • Zhao, Weirui & Yan, Anzhi, 2009. "Stability analysis of neural networks with both variable and unbounded delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(2), pages 697-707.
    • Handle: RePEc:eee:chsofr:v:40:y:2009:i:2:p:697-707
    DOI: 10.1016/j.chaos.2007.08.017
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077907006285
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2007.08.017?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. Lien, Chang-Hua & Chung, Long-Yeu, 2007. "Global asymptotic stability for cellular neural networks with discrete and distributed time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 34(4), pages 1213-1219.
    2. Wu, Wei & Cui, Bao Tong & Huang, Min, 2007. "Global asymptotic stability of delayed Cohen–Grossberg neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 34(3), pages 872-877.
    3. Arik, Sabri, 2005. "Global robust stability analysis of neural networks with discrete time delays," Chaos, Solitons & Fractals, Elsevier, vol. 26(5), pages 1407-1414.
    4. Huang, Zai-Tang & Luo, Xiao-Shu & Yang, Qi-Gui, 2007. "Global asymptotic stability analysis of bidirectional associative memory neural networks with distributed delays and impulse," Chaos, Solitons & Fractals, Elsevier, vol. 34(3), pages 878-885.
    5. Singh, Vimal, 2007. "Some remarks on global asymptotic stability of neural networks with constant time delay," Chaos, Solitons & Fractals, Elsevier, vol. 32(5), pages 1720-1724.
    6. Chen, Zhang & Zhao, Donghua & Ruan, Jiong, 2007. "Dynamic analysis of high-order Cohen–Grossberg neural networks with time delay," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1538-1546.
    7. Yang, Haifeng & Chu, Tianguang & Zhang, Cishen, 2006. "Exponential stability of neural networks with variable delays via LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 30(1), pages 133-139.
    8. Huang, Tingwen & Li, Chuandong & Chen, Goong, 2007. "Stability of Cohen–Grossberg neural networks with unbounded distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 34(3), pages 992-996.
    9. Park, Ju H. & Cho, Hyun J., 2007. "A delay-dependent asymptotic stability criterion of cellular neural networks with time-varying discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 33(2), pages 436-442.
    10. Song, Qiankun & Zhao, Zhenjiang, 2005. "Global dissipativity of neural networks with both variable and unbounded delays," Chaos, Solitons & Fractals, Elsevier, vol. 25(2), pages 393-401.
    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. 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.

    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. Singh, Vimal, 2009. "Novel global robust stability criterion for neural networks with delay," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 348-353.
    2. Zhou, Jun & Zhao, Weirui & Lv, Xiaohong & Zhu, Huaping, 2011. "Stability analysis of almost periodic solutions for delayed neural networks without global Lipschitz activation functions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2440-2455.
    3. Xu, Liguang & Xu, Daoyi, 2009. "Exponential p-stability of impulsive stochastic neural networks with mixed delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 263-272.
    4. Souza, Fernando O. & Palhares, Reinaldo M. & Ekel, Petr Ya., 2009. "Novel stability criteria for uncertain delayed Cohen–Grossberg neural networks using discretized Lyapunov functional," Chaos, Solitons & Fractals, Elsevier, vol. 41(5), pages 2387-2393.
    5. 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.
    6. 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.
    7. Tian, Junkang & Xu, Dongsheng, 2009. "New asymptotic stability criteria for neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(4), pages 1916-1922.
    8. Ping, Zhao Wu & Lu, Jun Guo, 2009. "Global exponential stability of impulsive Cohen–Grossberg neural networks with continuously distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 41(1), pages 164-174.
    9. Zong, Guangdeng & Liu, Jia, 2009. "New delay-dependent global robust stability conditions for interval neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(5), pages 2954-2964.
    10. Singh, Vimal, 2009. "Remarks on estimating upper limit of norm of delayed connection weight matrix in the study of global robust stability of delayed neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 39(5), pages 2013-2017.
    11. 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).
    12. Chen, Hao & Zhong, Shouming & Shao, Jinliang, 2015. "Exponential stability criterion for interval neural networks with discrete and distributed delays," Applied Mathematics and Computation, Elsevier, vol. 250(C), pages 121-130.
    13. 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.
    14. Xu, Jian & Chung, Kwok-Wai, 2009. "Dynamics for a class of nonlinear systems with time delay," Chaos, Solitons & Fractals, Elsevier, vol. 40(1), pages 28-49.
    15. Sun, Yeong-Jeu, 2007. "Duality between observation and output feedback for linear systems with multiple time delays," Chaos, Solitons & Fractals, Elsevier, vol. 33(3), pages 879-884.
    16. Park, Ju H., 2009. "Synchronization of cellular neural networks of neutral type via dynamic feedback controller," Chaos, Solitons & Fractals, Elsevier, vol. 42(3), pages 1299-1304.
    17. Rajavel, S. & Samidurai, R. & Cao, Jinde & Alsaedi, Ahmed & Ahmad, Bashir, 2017. "Finite-time non-fragile passivity control for neural networks with time-varying delay," Applied Mathematics and Computation, Elsevier, vol. 297(C), pages 145-158.
    18. Zhang, Qianhong & Luo, Wei, 2009. "Global exponential stability of fuzzy BAM neural networks with time-varying delays," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2239-2245.
    19. Gau, R.S. & Lien, C.H. & Hsieh, J.G., 2007. "Global exponential stability for uncertain cellular neural networks with multiple time-varying delays via LMI approach," Chaos, Solitons & Fractals, Elsevier, vol. 32(4), pages 1258-1267.
    20. Zhou, Xiaobing & Wu, Yue & Li, Yi & Yao, Xun, 2009. "Stability and Hopf bifurcation analysis on a two-neuron network with discrete and distributed delays," Chaos, Solitons & Fractals, Elsevier, vol. 40(3), pages 1493-1505.

    More about this item

    Statistics

    Access and download statistics

    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:40:y:2009:i:2:p:697-707. 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.