IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0204002.html
   My bibliography  Save this article

The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control

Author

Listed:
  • Weiping Wang
  • Xin Yu
  • Xiong Luo
  • Long Wang
  • Lixiang Li
  • Jürgen Kurths
  • Wenbing Zhao
  • Jiuhong Xiao

Abstract

In this paper, we propose a new model of memristive multidirectional associative memory neural networks, which concludes the time-varying delays in leakage terms via sampled-data control. We use the input delay method to turn the sampling system into a continuous time-delaying system. Then we analyze the exponential stability and asymptotic stability of the equilibrium points for this model. By constructing a suitable Lyapunov function, using the Lyapunov stability theorem and some inequality techniques, some sufficient criteria for ensuring the stability of equilibrium points are obtained. Finally, numerical examples are given to demonstrate the effectiveness of our results.

Suggested Citation

  • Weiping Wang & Xin Yu & Xiong Luo & Long Wang & Lixiang Li & Jürgen Kurths & Wenbing Zhao & Jiuhong Xiao, 2018. "The stability of memristive multidirectional associative memory neural networks with time-varying delays in the leakage terms via sampled-data control," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-26, September.
    • Handle: RePEc:plo:pone00:0204002
    DOI: 10.1371/journal.pone.0204002
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0204002
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0204002&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0204002?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
    ---><---

    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:plo:pone00:0204002. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.