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Robust stability results for uncertain stochastic neural networks with discrete interval and distributed time-varying delays. (English) Zbl 1223.92001
Summary: This Letter is concerned with the stability analysis problem for uncertain stochastic neural networks with discrete interval and distributed time-varying delays. The parameter uncertainties are assumed to be norm bounded and the delay is assumed to be time-varying and to belong to a given interval, which means that lower and upper bounds of interval time-varying delays are available. Based on the Lyapunov-Krasovskii functional and stochastic stability theory, delay-interval dependent stability criteria are obtained in terms of linear matrix inequalities. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI) and by introducing some free-weighting matrices. Finally, two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed LMI conditions.

92B20General theory of neural networks (mathematical biology)
93E15Stochastic stability
68T05Learning and adaptive systems
15A45Miscellaneous inequalities involving matrices
65C20Models (numerical methods)
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