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Global quasi-synchronisation of fuzzy cellular neural networks with time varying delay and interaction terms

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  • Ankit Kumar
  • Subir Das
  • Sapna Baluni
  • Vijay K. Yadav
  • Jianquan Lu

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.

Suggested Citation

  • Ankit Kumar & Subir Das & Sapna Baluni & Vijay K. Yadav & Jianquan Lu, 2022. "Global quasi-synchronisation of fuzzy cellular neural networks with time varying delay and interaction terms," International Journal of Systems Science, Taylor & Francis Journals, vol. 53(12), pages 2679-2693, September.
    • Handle: RePEc:taf:tsysxx:v:53:y:2022:i:12:p:2679-2693
    DOI: 10.1080/00207721.2022.2058109
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    Cited by:

    1. Kumar, Ankit & Das, Subir & Singh, Sunny & Rajeev,, 2023. "Quasi-projective synchronization of inertial complex-valued recurrent neural networks with mixed time-varying delay and mismatched parameters," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).

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