IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v74y2007i1p38-46.html
   My bibliography  Save this article

Global robust stability of interval neural networks with multiple time-varying delays

Author

Listed:
  • Song, Qiankun
  • Cao, Jinde

Abstract

In this paper, the global robust stability is investigated for interval neural networks with multiple time-varying delays. The neural network contains time-invariant uncertain parameters whose values are unknown but bounded in given compact sets. Without assuming both the boundedness on the activation functions and the differentiability on the time-varying delays, a new sufficient condition is presented to ensure the existence, uniqueness, and global robust stability of equilibria for interval neural networks with multiple time-varying delays based on the Lyapunov–Razumikhin technique as well as matrix inequality analysis. Several previous results are improved and generalized, and an example is given to show the effectiveness of the obtained results.

Suggested Citation

  • Song, Qiankun & Cao, Jinde, 2007. "Global robust stability of interval neural networks with multiple time-varying delays," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 74(1), pages 38-46.
    • Handle: RePEc:eee:matcom:v:74:y:2007:i:1:p:38-46
    DOI: 10.1016/j.matcom.2006.06.030
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037847540600214X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.matcom.2006.06.030?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.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liu, Leipo & Han, Zhengzhi & Cai, Xiushan & Huang, Jun, 2010. "Robust stabilization of linear differential inclusion system with time delay," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(5), pages 951-958.
    2. Zhu, Song & Shen, Yi & Chen, Guici, 2012. "Noise suppress exponential growth for hybrid Hopfield neural networks," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 86(C), pages 10-20.
    3. Samidurai, R. & Sriraman, R., 2019. "Robust dissipativity analysis for uncertain neural networks with additive time-varying delays and general activation functions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 155(C), pages 201-216.

    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:74:y:2007:i:1:p:38-46. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.