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A framework of YOLOv5 integrated privacy-preserving secure image communication using fractional order memristor based Chua’s circuit and fully synchronization with adaptive coupling strength

Author

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  • Babu Dhivakaran, P.
  • Vinodkumar, A.
  • Sriramakrishnan, P.
  • Alzabut, J.

Abstract

This paper demonstrates the fully distributed synchronization of fractional-order memristor-based Chua’s circuits with adaptive coupling strength. The outcome of the traditional and proposed circuits is applied for privacy-preserving victim data encryption with secure image communications using artificial intelligence through the YOLOv5 model. Finally, the application framework and its results depict the effectiveness of the theoretical parts. The results were measured using signal-to-noise ratio (SNR), peak signal-to-noise ratio (PSNR), and structural similarity index metrics (SSIM) and compared with several state-of-the-art methods. The result shows that the composite memristor Chua’s circuit and direct, undirected network yield higher accuracy at the receiver end compared to the traditional Chua’s Circuit and other existing models.

Suggested Citation

  • Babu Dhivakaran, P. & Vinodkumar, A. & Sriramakrishnan, P. & Alzabut, J., 2026. "A framework of YOLOv5 integrated privacy-preserving secure image communication using fractional order memristor based Chua’s circuit and fully synchronization with adaptive coupling strength," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 240(C), pages 284-302.
    • Handle: RePEc:eee:matcom:v:240:y:2026:i:c:p:284-302
    DOI: 10.1016/j.matcom.2025.07.005
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    References listed on IDEAS

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    1. Martín-Hernández, J. & Wang, H. & Van Mieghem, P. & D’Agostino, G., 2014. "Algebraic connectivity of interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 92-105.
    2. P. Babu Dhivakaran & A. Vinodkumar & S. Vijay & S. Lakshmanan & J. Alzabut & R. A. El-Nabulsi & W. Anukool, 2022. "Bipartite Synchronization of Fractional-Order Memristor-Based Coupled Delayed Neural Networks with Pinning Control," Mathematics, MDPI, vol. 10(19), pages 1-13, October.
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