New results of global Mittag-Leffler synchronization on Caputo fuzzy delayed inertial neural networks
Articles
Xiangnian Yin
Anqing Normal University
Hongmei Zhang
Anqing Normal University
Hai Zhang
Anqing Normal University
Weiwei Zhang
Anqing Normal University
https://orcid.org/0000-0001-5316-9721
Jinde Cao
Southeast University
Published 2023-03-30
https://doi.org/10.15388/namc.2023.28.31878
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Keywords

Caputo derivative
global Mittag-Leffler synchronization
fuzzy inertial neural networks
variable substitution

How to Cite

Yin, X. (2023) “New results of global Mittag-Leffler synchronization on Caputo fuzzy delayed inertial neural networks”, Nonlinear Analysis: Modelling and Control, 28(4), pp. 613–631. doi:10.15388/namc.2023.28.31878.

Abstract

This article is devoted to discussing the problem of global Mittag-Leffler synchronization (GMLS) for the Caputo-type fractional-order fuzzy delayed inertial neural networks (FOFINNs). First of all, both inertial and fuzzy terms are taken into account in the system. For the sake of reducing the influence caused by the inertia term, the order reduction is achieved by the measure of variable substitution. The introduction of fuzzy terms can evade fuzziness or uncertainty as much as possible. Subsequently, a nonlinear delayed controller is designed to achieve GMLS. Utilizing the inequality techniques, Lyapunov’s direct method for functions and Razumikhin theorem, the criteria for interpreting the GMLS of FOFINNs are established. Particularly, two inferences are presented in two special cases. Additionally, the availability of the acquired results are further confirmed by simulations.

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