IDEAS home Printed from https://ideas.repec.org/a/hin/jnlaaa/109319.html
   My bibliography  Save this article

Global Convergence for Cohen-Grossberg Neural Networks with Discontinuous Activation Functions

Author

Listed:
  • Yanyan Wang
  • Jianping Zhou

Abstract

Cohen-Grossberg neural networks with discontinuous activation functions is considered. Using the property of -matrix and a generalized Lyapunov-like approach, the uniqueness is proved for state solutions and corresponding output solutions, and equilibrium point and corresponding output equilibrium point of considered neural networks. Meanwhile, global exponential stability of equilibrium point is obtained. Furthermore, by contraction mapping principle, the uniqueness and globally exponential stability of limit cycle are given. Finally, an example is given to illustrate the effectiveness of the obtained results.

Suggested Citation

  • Yanyan Wang & Jianping Zhou, 2012. "Global Convergence for Cohen-Grossberg Neural Networks with Discontinuous Activation Functions," Abstract and Applied Analysis, Hindawi, vol. 2012, pages 1-14, November.
    • Handle: RePEc:hin:jnlaaa:109319
    DOI: 10.1155/2012/109319
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/AAA/2012/109319.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/AAA/2012/109319.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2012/109319?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:hin:jnlaaa:109319. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.