New Approach to Quasi-Synchronization of Fractional-Order Delayed Neural Networks

Author:

Zhang Shilong1,Du Feifei1ORCID,Chen Diyi2

Affiliation:

1. College of Science, Northwest A&F University, Yangling 712100, China

2. Institute of Water Resources and Hydropower Research, Northwest A&F University, Yangling 712100, China

Abstract

This article investigates quasi-synchronization for a class of fractional-order delayed neural networks. By utilizing the properties of the Laplace transform, the Caputo derivative, and the Mittag–Leffler function, a new fractional-order differential inequality is introduced. Furthermore, an adaptive controller is designed, resulting in the derivation of an effective criterion to ensure the aforementioned synchronization. Finally, a numerical illustration is provided to demonstrate the validity of the presented theoretical findings.

Funder

Natural Science Basic Research Program in Shaanxi Province of China

Shaanxi Fundamental Science Research Project for Mathematics and Physics

Chinese Universities Scientific Fund

Publisher

MDPI AG

Subject

Statistics and Probability,Statistical and Nonlinear Physics,Analysis

Reference52 articles.

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