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New Results of Global Asymptotical Stability for Impulsive Hopfield Neural Networks with Leakage Time-Varying Delay

New Results of Global Asymptotical Stability for Impulsive Hopfield Neural Networks with Leakage Time-Varying Delay
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摘要 In this paper, Hopfield neural networks with impulse and leakage time-varying delay are considered. New sufficient conditions for global asymptotical stability of the equilibrium point are derived by using Lyapunov-Kravsovskii functional, model transformation and some analysis techniques. The criterion of stability depends on the impulse and the bounds of the leakage time-varying delay and its derivative, and is presented in terms of a linear matrix inequality (LMI). In this paper, Hopfield neural networks with impulse and leakage time-varying delay are considered. New sufficient conditions for global asymptotical stability of the equilibrium point are derived by using Lyapunov-Kravsovskii functional, model transformation and some analysis techniques. The criterion of stability depends on the impulse and the bounds of the leakage time-varying delay and its derivative, and is presented in terms of a linear matrix inequality (LMI).
作者 Qiang Xi
出处 《Journal of Applied Mathematics and Physics》 2017年第11期2112-2126,共15页 应用数学与应用物理(英文)
关键词 Global Asymptotical Stability HOPFIELD Neural Networks LEAKAGE Time-Varying Delay IMPULSE Lyapunov-Kravsovskii Functional Linear Matrix INEQUALITY Global Asymptotical Stability Hopfield Neural Networks Leakage Time-Varying Delay Impulse Lyapunov-Kravsovskii Functional Linear Matrix Inequality
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