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Exponential and fixed‐time stabilization of memristive neural networks with mixed delays

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In this paper, we study a class of memristive neural networks with mixed delays. The existence of its equilibrium point is proved without the boundedness and initial value of the… Click to show full abstract

In this paper, we study a class of memristive neural networks with mixed delays. The existence of its equilibrium point is proved without the boundedness and initial value of the activation function, and a criterion to ensure its exponential stabilization under a sampled‐data controller is obtained by constructing an appropriate Lyapunov function. Meanwhile, the fixed‐time stabilization of memristive neural networks is also proved by the Lyapunov method. The obtained results extend and enhance some existing ones, and are illustrated by numerical examples.

Keywords: neural networks; mixed delays; networks mixed; memristive neural; stabilization; fixed time

Journal Title: Mathematical Methods in the Applied Sciences
Year Published: 2021

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