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

Author

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  • Yao-Qun Xu
  • Xin-Xin Zhen
  • Meng Tang

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, 2022. "Dynamical System in Chaotic Neurons with Time Delay Self‐Feedback and Its Application in Color Image Encryption," Complexity, John Wiley & Sons, vol. 2022(1).
    • Handle: RePEc:wly:complx:v:2022:y:2022:i:1:n:2832104
    DOI: 10.1155/2022/2832104
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    References listed on IDEAS

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    1. Ibrahim Yasser & Fahmi Khalifa & Mohamed A. Mohamed & Ahmed S. Samrah, 2020. "A New Image Encryption Scheme Based on Hybrid Chaotic Maps," Complexity, Hindawi, vol. 2020, pages 1-23, July.
    2. Khalid A. Alattas & Javad Mostafaee & Aceng Sambas & Abdullah K. Alanazi & Saleh Mobayen & Mai The Vu & Anton Zhilenkov, 2021. "Nonsingular Integral-Type Dynamic Finite-Time Synchronization for Hyper-Chaotic Systems," Mathematics, MDPI, vol. 10(1), pages 1-21, December.
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