Mittag-Leffler synchronization in finite time of fractional-order discrete-time quaternion-valued neural networks via quantized control and its application

Weiwei Cheng, Weiwei Zhang, Hai Zhang, Ivanka Stamova and Jinde Cao

Mathematics and Computers in Simulation (MATCOM), 2026, vol. 248, issue C, 362-383

Abstract: This paper investigates the finite-time Mittag-Leffler synchronization (FTMLS) of a class of fractional-order discrete-time quaternion-valued neural networks (FODTQNNs) via quantized control. Initially, a FODTQNNs incorporating time delay is established. Due to the strong robustness and adaptability of quantized controllers, we design two types of quantized controllers. Moreover, we combine the quantized controller with an adaptive controller, which significantly reduces control costs. The conditions for finite-time synchronization are derived through the application of inequality techniques and the Razumikhin theorem, by selecting appropriate Lyapunov functions. Eventually, numerical simulations are employed to demonstrate the feasibility of the theoretical analysis presented, and a potential application in image secure communication is presented, demonstrating the practical value of the proposed approach.

Keywords: Quantized control; Adaptive control; Fractional-order quaternion-valued neural network; Discrete-time (search for similar items in EconPapers)
Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:248:y:2026:i:c:p:362-383

DOI: 10.1016/j.matcom.2026.04.016

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