Anti–Periodic Solutions for Clifford–Valued High–Order Hopfield Neural Networks with State–Dependent and Leakage Delays

Huo, Nina; Li, Bing; Li, Yongkun

doi:10.34768/amcs-2020-0007

Abstract

A class of Clifford-valued high-order Hopfield neural networks (HHNNs) with state-dependent and leakage delays is considered. First, by using a continuation theorem of coincidence degree theory and the Wirtinger inequality, we obtain the existence of anti-periodic solutions of the networks considered. Then, by using the proof by contradiction, we obtain the global exponential stability of the anti-periodic solutions. Finally, two numerical examples are given to illustrate the feasibility of our results.

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Anti–Periodic Solutions for Clifford–Valued High–Order Hopfield Neural Networks with State–Dependent and Leakage Delays

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