$ S $-asymptotically $ \omega $-periodic dynamics in a fractional-order dual inertial neural networks with time-varying lags

Huizhen Qu; Jianwen Zhou; Huizhen Qu; Jianwen Zhou

doi:10.3934/math.2022154

AIMS Mathematics

2022, Volume 7, Issue 2: 2782-2809. doi: 10.3934/math.2022154

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$ S $-asymptotically $ \omega $-periodic dynamics in a fractional-order dual inertial neural networks with time-varying lags

Huizhen Qu ,
Jianwen Zhou ^,

Department of Mathematics, Yunnan University, Kunming, Yunnan 650091, China

Received: 27 July 2021 Accepted: 16 November 2021 Published: 19 November 2021
MSC : 34C25, 34K20

This paper investigates global dynamics in fractional-order dual inertial neural networks with time lags. Firstly, according to some crucial features of Mittag-Leffler functions and Banach contracting mapping principle, the existence and uniqueness of $ S $-asymptotically $ \omega $-periodic oscillation of the model are gained. Secondly, by using the comparison principle and the stability criteria of delayed Caputo fractional-order differential equations, global asymptotical stability of the model is studied. In the end, the feasibility and effectiveness of the obtained conclusions are supported by two numerical examples. There are few papers focus on $ S $-asymptotically $ \omega $-periodic dynamics in fractional-order dual inertial neural networks with time-varying lags, apparently, the works in this paper fill some of the gaps.
- inertial,
- neural network,
- mittag-leffler,
- global asymptotical stability,
- $ S $-asymptotical periodicity
Citation: Huizhen Qu, Jianwen Zhou. $ S $-asymptotically $ \omega $-periodic dynamics in a fractional-order dual inertial neural networks with time-varying lags[J]. AIMS Mathematics, 2022, 7(2): 2782-2809. doi: 10.3934/math.2022154

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Abstract

This paper investigates global dynamics in fractional-order dual inertial neural networks with time lags. Firstly, according to some crucial features of Mittag-Leffler functions and Banach contracting mapping principle, the existence and uniqueness of $ S $-asymptotically $ \omega $-periodic oscillation of the model are gained. Secondly, by using the comparison principle and the stability criteria of delayed Caputo fractional-order differential equations, global asymptotical stability of the model is studied. In the end, the feasibility and effectiveness of the obtained conclusions are supported by two numerical examples. There are few papers focus on $ S $-asymptotically $ \omega $-periodic dynamics in fractional-order dual inertial neural networks with time-varying lags, apparently, the works in this paper fill some of the gaps.

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