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New results on finite-/fixed-time synchronization of delayed memristive neural networks with diffusion effects
AIMS Mathematics 2022, 7(9): 16962-16974
Published: 15 September 2022
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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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