Robust fixed-time synchronization of discontinuous Cohen–Grossberg neural networks with mixed time delays

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ISSN: 1392-5113
E-ISSN: 2335-8963

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Vilnius University Press
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This paper aims to investigate the fixed-time synchronization (i.e., synchronization in fixed-time sense) of Cohen–Grossberg drive-response neural networks with discontinuous neuron activations and mixed time delays (both time-varying discrete delay and distributed delay). To accomplish the target of fixed-time synchronization, a novel discontinuous feedback control procedure is firstly designed for the response neural networks. Then, under the framework of Filippov solutions, by means of functional differential inclusions theory, inequality technique and the nonsmooth analysis theory with Lyapunov-like approach, some sufficient criteria are derived to design the control parameters for achieving fixed-time synchronization of the proposed drive-response systems. Finally, two numerical examples are presented to illustrate the proposed methodologies

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Kong F., Zhu Q., Liang F. and Nieto J. J. (2019) “Robust fixed-time synchronization of discontinuous Cohen–Grossberg neural networks with mixed time delays”, Nonlinear Analysis: Modelling and Control, 24(4), pp. 603–625. doi: 10.15388/NA.2019.4.7

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© 2019 Authors. Published by Vilnius University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited