Anti-synchronization of fractional-order complex-valued neural networks with a leakage delay and time-varying delays

Xuemei Li, Xinge Liu and Fengxian Wang

Chaos, Solitons & Fractals, 2023, vol. 174, issue C

Abstract: In this paper, the anti-synchronization for fractional-order complex-valued neural networks (FCVNNs) with a leakage delay and time-varying delays is investigated. The solution of a fractional-order differential inequality is considered. By using the Laplace transform and the inverse Laplace transform, a new inequality is proved, which provides an important tool for studying the anti-synchronization of the FCVNNs with delays. Two different types of controllers are designed. Based on this new inequality and some inequality techniques, several sufficient conditions are obtained to ensure the anti-synchronization of the FCVNNs with a leakage term and time-varying delays. Finally, two numerical examples are presented to illustrate the validity and feasibility of the main results.

Keywords: Anti-synchronization; Fractional-order; Complex-valued neural networks; Leakage delay; Time-varying delays (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:174:y:2023:i:c:s0960077923006550

DOI: 10.1016/j.chaos.2023.113754

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