IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v65y2014icp90-96.html
   My bibliography  Save this article

Integral manifolds for uncertain impulsive differential–difference equations with variable impulsive perturbations

Author

Listed:
  • Stamov, Gani Tr.
  • Stamova, Ivanka M.

Abstract

In the present paper sufficient conditions for the existence of integral manifolds of uncertain impulsive differential–difference equations with variable impulsive perturbations are obtained. The investigations are carried out by means the concepts of uniformly positive definite matrix functions, Hamilton–Jacobi–Riccati inequalities and piecewise continuous Lyapunov’s functions.

Suggested Citation

  • Stamov, Gani Tr. & Stamova, Ivanka M., 2014. "Integral manifolds for uncertain impulsive differential–difference equations with variable impulsive perturbations," Chaos, Solitons & Fractals, Elsevier, vol. 65(C), pages 90-96.
    • Handle: RePEc:eee:chsofr:v:65:y:2014:i:c:p:90-96
    DOI: 10.1016/j.chaos.2014.05.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077914000812
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2014.05.002?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. Gani Stamov & Ivanka Stamova & George Venkov & Trayan Stamov & Cvetelina Spirova, 2020. "Global Stability of Integral Manifolds for Reaction–Diffusion Delayed Neural Networks of Cohen–Grossberg-Type under Variable Impulsive Perturbations," Mathematics, MDPI, vol. 8(7), pages 1-18, July.
    2. Peng, Cheng & Liu, Xiaoqi & Kang, Rui & Wang, Sihan & Gao, Shang, 2023. "Stochastic input-to-state stability for stochastic complex dynamical control networks with impulsive perturbation," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    3. Gani Stamov & Ivanka Stamova & Stanislav Simeonov & Ivan Torlakov, 2020. "On the Stability with Respect to H-Manifolds for Cohen–Grossberg-Type Bidirectional Associative Memory Neural Networks with Variable Impulsive Perturbations and Time-Varying Delays," Mathematics, MDPI, vol. 8(3), pages 1-14, March.

    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:65:y:2014:i:c:p:90-96. 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: 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.