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Image of Journal of Applied Nonlinear Dynamics
ISSN:2164-6457 (print)
ISSN:2164-6473 (online)
Journal of Applied Nonlinear Dynamics
Miguel A. F. Sanjuan (editor), Albert C.J. Luo (editor)
Miguel A. F. Sanjuan (editor)

Department of Physics, Universidad Rey Juan Carlos, 28933 Mostoles, Madrid, Spain

Email: miguel.sanjuan@urjc.es

Albert C.J. Luo (editor)

Department of Mechanical and Industrial Engineering, Southern Illinois University Ed-wardsville, IL 62026-1805, USA

Fax: +1 618 650 2555 Email: aluo@siue.edu

Dual Synchronization of Fractional-Order Complex-Valued Neural Networks with Application to Medical Image Encryption

Journal of Applied Nonlinear Dynamics 15(2) (2026) 361--374 | DOI:10.5890/JAND.2026.06.008

Hadjer Zerimeche$^1$, Tarek Houmor$^{2}$

$^1$ Department of Mathematics, Faculty of Exact Sciences, Fr`eres Mentouri University, Constantine 25017, Algeria

$^2$ Laboratory of Applied Mathematics and Modeling, Department of Mathematics, Faculty of Exact Sciences, Fr`eres Mentouri University, Constantine 25017, Algeria

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Abstract

This paper explores a novel dual synchronization method for fractional-order complex-valued neural networks (FOCVNN) by combining adaptive control, inequality techniques, and stability theory of fractional calculus. The FOCVNN are separated into two real-valued parts and two imaginary-valued parts. According to the proposed dual synchronization scheme, a chaotic masking method is suggested for encrypting medical images to preserve patient information. Simulation results demonstrate the efficiency of the control laws and parameter updating equations. Additionally, experimental results including histograms, change rate of the number of pixels in the cipher-image (NPCR), unified average changing intensity (UACI), peak signal-to-noise ratio (PSNR) and correlation confirm the effectiveness of the proposed method for secure image communication.

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