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• W2489521723 abstract "This paper investigates the problem of robust finite time stabilization for a uncertain neural networks with leakage delay and probabilistic time-varying delays. By introducing a stochastic variable which satisfies Bernoulli distribution, the information of probabilistic time-varying delay is equivalently transformed into the deterministic time-varying delay with stochastic parameters. The main objective of this paper is to design a memoryless state feedback control such that the resulting proposed system is robustly finite time stable with admissible uncertainties. Based on a suitable Lyapunov–Krasovskii functional, model transformation technique and Wirtinger-based double integral inequality, the general framework is obtained in terms of linear matrix inequalities to determine the finite time stability and to achieve the control design. Finally, three numerical examples are presented to validate the effectiveness and less conservatism of the proposed method." @default.
• W2489521723 created "2016-08-23" @default.
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• W2489521723 date "2016-11-01" @default.
• W2489521723 modified "2023-09-30" @default.
• W2489521723 title "Robust finite time stabilization analysis for uncertain neural networks with leakage delay and probabilistic time-varying delays" @default.
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• W2489521723 doi "https://doi.org/10.1016/j.jfranklin.2016.07.006" @default.
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