IDEAS home Printed from https://ideas.repec.org/a/taf/tsysxx/v53y2022i11p2281-2300.html
   My bibliography  Save this article

Global asymptotic synchronisation of fuzzy inertial neural networks with time-varying delays by applying maximum-value approach

Author

Listed:
  • Zhen Yang
  • Zhengqiu Zhang

Abstract

In the paper, we are concerned about the global asymptotic synchronisation for a class of fuzzy master–slave inertial neural networks with time-varying delays. At present, most of the research on the global asymptotic synchronisation of fuzzy master–slave inertial neural networks with time-varying delays adopt the matrix measure method, linear matrix inequality approach and integral inequality method. While in our paper, we attain three criteria to assure the global asymptotic synchronisation between the master system and the slave system by designing three classes of different novel controllers via the maximum-value analysis approach. The controllers designed and the maximum-value method used in this paper are completely novel compared with these in the existing literatures, which enrich and extend the published results.

Suggested Citation

  • Zhen Yang & Zhengqiu Zhang, 2022. "Global asymptotic synchronisation of fuzzy inertial neural networks with time-varying delays by applying maximum-value approach," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(11), pages 2281-2300, August.
    • Handle: RePEc:taf:tsysxx:v:53:y:2022:i:11:p:2281-2300
    DOI: 10.1080/00207721.2022.2050437
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00207721.2022.2050437
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00207721.2022.2050437?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. Chen, Dazhao & Zhang, Zhengqiu, 2022. "Globally asymptotic synchronization for complex-valued BAM neural networks by the differential inequality way," Chaos, Solitons & Fractals, Elsevier, vol. 164(C).

    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:taf:tsysxx:v:53:y:2022:i:11:p:2281-2300. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/TSYS20 .

    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.