Robust fixed-time synchronization of discontinuous Cohen–Grossberg neural networks with mixed time delays
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Vilnius University Press
Abstract
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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https://doi.org/10.15388/NA.2019.4.7Sponsors
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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








