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The global robust exponential stability in mean square for a class of stochastic neural networks with distributed delays and polytopic uncertainties is investigated in this paper. Parameter-dependent Lypaunov-Krasovskii functionals and free-weighting matrices are employed to obtain sufficient condition that guarantee the robust global exponential stability the considered stochastic neural networks...
This paper is concerned with the asymptotic stability analysis problem for stochastic neural networks with distributed and time-varying delays. By using the stochastic analysis approach, employing some free-weighting matrices and introducing an appropriate type of Lyapunov functional which take into account the ranges of delays, a new stability criterion is established in terms of linear matrix inequalities...
In this letter, the global asymptotical stability analysis problem is considered for a class of Markovian jumping stochastic Cohen-Grossberg neural networks (CGNNs) with mixed delays including discrete delays and distributed delays. An alternative delay-dependent stability analysis result is established based on the linear matrix inequality (LMI) technique, which can easily be checked by utilizing...
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