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Research Article | Open Access

Modified function projective synchronization of master-slave neural networks with mixed interval time-varying delays via intermittent feedback control

Rakkiet SrisuntornWajaree WeeraThongchai Botmart( )
Department of Mathematics, Khon Kaen University, Khon Kaen 40002, Thailand
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Abstract

The modified function projective synchronization problem for master-slave neural networks with mixed interval time-varying delays is presented using periodically intermittent feedback control. The interval distributed time-varying delay including the lower and upper bound is comprehensively established, which developed from the previous work. The following techniques are utilize to analyze the appropriate criteria for the modified function projective synchronization problem for master-slave neural networks with mixed interval time-varying delays such as the construction of appropriate Lyapunov-Krasovskii functionals merged with Newton-Leibniz formulation method, the intermittent feedback control technique, the reciprocally convex technique's lower bound lemma, Jensen's inequality, and the piecewise analytic method. The sufficient criteria for the modified function projective synchronization of the error system between the master and slave neural networks with intermittent feedback control are first established in terms of linear matrix inequalities (LMIs). The designed controller ensures that the synchronization of the error systems are proposed via intermittent feedback control. Finally, numerical examples are given to demonstrate the effectiveness of the proposed method.

CLC number: 34D06, 92B20, 93B52

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AIMS Mathematics
Pages 18632-18661

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Cite this article:
Srisuntorn R, Weera W, Botmart T. Modified function projective synchronization of master-slave neural networks with mixed interval time-varying delays via intermittent feedback control. AIMS Mathematics, 2022, 7(10): 18632-18661. https://doi.org/10.3934/math.20221025

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Received: 15 June 2022
Revised: 07 August 2022
Accepted: 15 August 2022
Published: 15 October 2022
©2022 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)