Global quasi-synchronisation of fuzzy cellular neural networks with time varying delay and interaction terms
Ankit Kumar,
Subir Das,
Sapna Baluni,
Vijay K. Yadav and
Jianquan Lu
International Journal of Systems Science, 2022, vol. 53, issue 12, 2679-2693
Abstract:
In this article, the global quasi-synchronisation of fuzzy cellular neural networks (FCNNs) in the presence of interaction terms and time-varying delay has been studied. The quasi-synchronisation criteria of FCNNs have been found with the help of p-norm and inequalities defined in Lemmas 2.1 and 2.2. Under the Lyapunov stability theory, the quasi-synchronisation of fuzzy-based CNNs with time-varying delay and interaction terms is attained using state-feedback controllers. A significant result for the two nonidentical FCNNs with time varying delay and interaction terms is provided. The error bounds of the global quasi-synchronisation have also been estimated. It is also seen that the global quasi-synchronisation of FCNNs is quite new. Two numerical simulation results are given to exhibit the viability and unwavering quality of the obtained results under several conditions.
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:53:y:2022:i:12:p:2679-2693
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DOI: 10.1080/00207721.2022.2058109
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