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oaioai:doaj.org/article:5ab2e423130e4f5ea0a3ab2235f58485

New results on finite-/fixed-time synchronization of delayed memristive neural networks with diffusion effects

Authors
Publication date
1 July 2022
Publisher
'American Institute of Mathematical Sciences (AIMS)'
Doi

    Abstract

    In this paper, we further investigate the finite-/fixed-time synchronization (FFTS) problem for a class of delayed memristive reaction-diffusion neural networks (MRDNNs). By utilizing the state-feedback control techniques, and constructing a general Lyapunov functional, with the help of inequality techniques and the finite-time stability theory, novel criteria are established to realize the FFTS of the considered delayed MRDNNs, which generalize and complement previously known results. Finally, a numerical example is provided to support the obtained theoretical results

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    Last time updated on 24/11/2022

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