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