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• W2159971699 abstract "This paper performs a global stability analysis of a particular class of recurrent neural networks (RNN) with time-varying delay. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities (LMI) through the use of Leibniz-Newton formula and relaxation matrices. Finally, two numerical examples are given to illustrate the effectiveness of the given criterion." @default.
• W2159971699 created "2016-06-24" @default.
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• W2159971699 date "2008-06-01" @default.
• W2159971699 modified "2023-09-26" @default.
• W2159971699 title "Design of delay-range-dependent state estimators for discrete-time recurrent neural networks with interval time-varying delay" @default.
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• W2159971699 doi "https://doi.org/10.1109/acc.2008.4587154" @default.
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