A novel fixed-time stability strategy and its application to fixed-time synchronization control of semi-Markov jump delayed neural networks

This paper emphasizes on a novel fixed-time stability strategy and its application to fixed-time synchronization control for a class of semi-Markov jump delayed Cohen-Grossberg neural networks (SMJDCGNNs). First, a novel fixed-time stability strategy for a class of nonlinear delayed systems is propo...

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Bibliographic Details
Published in:Neurocomputing (Amsterdam) 2021-09, Vol.452, p.284-293
Main Authors: Wang, Xin, Cao, Jinde, Wang, Jiangtao, Qi, Jinshan
Format: Article
Language:English
Subjects:
Cohen-Grossberg neural networks
Delayed systems
Fixed-time stability strategy
Semi-Markov jump
Settling time
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Summary:This paper emphasizes on a novel fixed-time stability strategy and its application to fixed-time synchronization control for a class of semi-Markov jump delayed Cohen-Grossberg neural networks (SMJDCGNNs). First, a novel fixed-time stability strategy for a class of nonlinear delayed systems is proposed, which is a generalization of the existing stability strategies. Second, the addressed fixed-time stability strategy is applied to solving fixed-time synchronization control for a class of SMJDCGNNs, whose framework generalizes the existing Cohen-Grossberg neural networks (CGNNs). The application testifies that compared with the existing fixed-time stability strategies, the obtained fixed-time stability strategy can provide a tighter settling time which can more effectively and accurately estimate the convergence time of the studied delayed system. Finally, we give a comparative example to illustrate the validity of our results.
ISSN:0925-2312
1872-8286
DOI:10.1016/j.neucom.2021.04.107