 Mittag-Leffler synchronization of fractional-order coupled neural networks with mixed delaysBibo Zheng and Zhanshan Wang Applied Mathematics and Computation, 2022, vol. 430, issue C Abstract: This paper is devoted to investigating Mittag-Leffler synchronization of fractional-order coupled neural networks (FOCNNs) with mixed delays, where the time-varying delays and infinite distributed delays are both taken into account. Firstly, a universal delayed FOCNNs model is introduced, which includes several FOCNNs with various time delays structures such as distributed delays and constant delays or time-varying delays, as its special cases. Besides, for the case where the existing results cannot be applied to infinite time delays, a generalized fractional-order Halanay inequality is proposed, which facilitates the analysis of synchronization of FOCNNs. Based on the generalized inequality, a unified synchronization analysis framework for FOCNNs is established, which is also applied to the cases with commonly considered FOCNNs with distribute delays, constant or time-varying delays. All the derived synchronization criteria have similar results and can be easily verified. Finally, a numerical example is provided to show the effectiveness of obtained results. Keywords: Coupled neural networks; Fractional-order; Mittag-Leffler synchronization; Mixed time delays (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:430:y:2022:i:c:s0096300322003770 DOI: 10.1016/j.amc.2022.127303 Access Statistics for this article Applied Mathematics and Computation is currently edited by Theodore Simos More articles in Applied Mathematics and Computation from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.