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Finite-time Synchronization of Fuzzy Cellular Neural Networks with Stochastic Perturbations and Mixed Delays

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Abstract

This paper investigates finite-time synchronization for fuzzy cellular neural networks (FCNNs). In contrast to correlative studies, discrete time delays, distributed delays and stochastic perturbations are taken into consideration. A mathematical model of this kind of FCNN is considered for the first time. By employing the Lyapunov method, graph theory, the feedback control technique and stochastic finite-time synchronization theory, several sufficient conditions for finite-time synchronization of FCNNs are derived. The upper bound of the stochastic settling time is explicitly proposed and has a close relationship with the topological structure of the neural network. Finally, a numerical example is used to validate the practicability and feasibility of the theoretical results we propose.

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Funding

This work is supported by the Fundamental Research Funds for the Central Universities (No.2572020BC09).

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Authors and Affiliations

  1. Department of Mathematics, Northeast Forestry University, Harbin, 150040, Heilongjiang, People’s Republic of China

    Dongsheng Xu & Ming Liu

  2. Department of Mathematics, Harbin Institute of Technology (Weihai), Weihai, 264209, People’s Republic of China

    Ting Wang

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  1. Dongsheng Xu
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Correspondence to Ming Liu.

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Xu, D., Wang, T. & Liu, M. Finite-time Synchronization of Fuzzy Cellular Neural Networks with Stochastic Perturbations and Mixed Delays. Circuits Syst Signal Process 40, 3244–3265 (2021). https://doi.org/10.1007/s00034-020-01631-3

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