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• W2017753607 abstract "In the paper, the problem of robust exponential stability analysis is investigated for stochastic Cohen–Grossberg neural networks with both interval time-varying and distributed time-varying delays. By employing an augmented Lyapunov–Krasovskii functional, together with the LMI approach and definition on convex set, two delay-dependent conditions guaranteeing the robust exponential stability (in the mean square sense) of addressed system are presented. Additionally, the activation functions are of more general descriptions and the derivative of time-varying delay being less than 1 is released, which generalize and further improve those earlier methods. Numerical examples are provided to demonstrate the effectiveness of proposed stability conditions." @default.
• W2017753607 created "2016-06-24" @default.
• W2017753607 creator A5047786998 @default.
• W2017753607 creator A5048327458 @default.
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• W2017753607 date "2009-12-01" @default.
• W2017753607 modified "2023-10-16" @default.
• W2017753607 title "Robust stability of stochastic Cohen–Grossberg neural networks with mixed time-varying delays" @default.
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• W2017753607 doi "https://doi.org/10.1016/j.neucom.2009.07.007" @default.
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