IDEAS home Printed from https://ideas.repec.org/a/hin/complx/2832104.html
   My bibliography  Save this article

Dynamical System in Chaotic Neurons with Time Delay Self-Feedback and Its Application in Color Image Encryption

Author

Listed:
  • Yao-Qun Xu
  • Xin-Xin Zhen
  • Meng Tang
  • Rosa M. Lopez Gutierrez

Abstract

The time delay caused by transmission in neurons is often ignored, but it is demonstrated by theories and practices that time delay is unavoidable. A new chaotic neuron model with time delay self-feedback is proposed based on Chen’s chaotic neuron. The bifurcation diagram and Lyapunov exponential diagram are used to analyze the chaotic characteristics of neurons in the model when they receive the output signals at different times. The experimental results exhibit that it has a rich dynamic behavior. In addition, the randomness of chaotic series generated by chaotic neurons with time delay self-feedback under different conditions is verified. In order to investigate the application of this model in image encryption, an image encryption scheme is proposed. The security analysis of the simulation results shows that the encryption algorithm has an excellent anti-attack ability. Therefore, it is necessary and practical to study chaotic neurons with time delay self-feedback.

Suggested Citation

  • Yao-Qun Xu & Xin-Xin Zhen & Meng Tang & Rosa M. Lopez Gutierrez, 2022. "Dynamical System in Chaotic Neurons with Time Delay Self-Feedback and Its Application in Color Image Encryption," Complexity, Hindawi, vol. 2022, pages 1-28, July.
    • Handle: RePEc:hin:complx:2832104
    DOI: 10.1155/2022/2832104
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/complexity/2022/2832104.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/complexity/2022/2832104.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/2832104?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:complx:2832104. 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.