Finite-time non-fragile control for synchronization of uncertain generalized neural networks with mixed two additive time-varying delays and general activation function

Volume 37, Issue 4, pp 465--486 https://dx.doi.org/10.22436/jmcs.037.04.08
Publication Date: November 14, 2024 Submission Date: August 15, 2024 Revision Date: August 31, 2024 Accteptance Date: September 20, 2024

Authors

C. Zamart - Department of Applied Mathematics and Statistics, Faculty of Science and Liberal Arts, Rajamangala University of Technology Isan, Nakhon Ratchasima 30000, Thailand. S. Luemsai - Department of Applied Mathematics and Statistics, Faculty of Science and Liberal Arts, Rajamangala University of Technology Isan, Nakhon Ratchasima 30000, Thailand. N. Yotha - Department of Applied Mathematics and Statistics, Faculty of Science and Liberal Arts, Rajamangala University of Technology Isan, Nakhon Ratchasima 30000, Thailand.


Abstract

This paper introduces novel delay-dependent criteria for achieving finite-time synchronization in generalized neural networks (GNNs) with uncertainties and mixed two additive time-varying delays. We incorporate non-fragile feedback control to enhance stability benchmarks. Our approach employs various methods, such as Jensen's inequality, an extended Jensen's double integral inequality, and an extended Wirtinger's integral inequality to estimate the derivative of the Lyapunov-Krasovskii functional (LKF). Moreover, a general activation function is considered to derive less conservative synchronization criteria of the GNNs with additive time-varying delays. Using a toolbox optimization in MATLAB, we derive and solve novel delay-dependent conditions in terms of linear matrix inequalities (LMIs). By stability criteria, this paper is less conservative than previous works. Finally, we give two numerical examples to show the advantages of our proposed methods.


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ISRP Style

C. Zamart, S. Luemsai, N. Yotha, Finite-time non-fragile control for synchronization of uncertain generalized neural networks with mixed two additive time-varying delays and general activation function, Journal of Mathematics and Computer Science, 37 (2025), no. 4, 465--486

AMA Style

Zamart C., Luemsai S., Yotha N., Finite-time non-fragile control for synchronization of uncertain generalized neural networks with mixed two additive time-varying delays and general activation function. J Math Comput SCI-JM. (2025); 37(4):465--486

Chicago/Turabian Style

Zamart, C., Luemsai, S., Yotha, N.. "Finite-time non-fragile control for synchronization of uncertain generalized neural networks with mixed two additive time-varying delays and general activation function." Journal of Mathematics and Computer Science, 37, no. 4 (2025): 465--486


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