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Stability analysis of switched stochastic neural networks with time-varying delays. (English) Zbl 1302.93235
Summary: This paper is concerned with the global exponential stability of switched stochastic neural networks with time-varying delays. Firstly, the stability of switched stochastic delayed neural networks with stable subsystems is investigated by utilizing the mathematical induction method, the piecewise Lyapunov function and the average dwell time approach. Secondly, by utilizing the extended comparison principle from impulsive systems, the stability of stochastic switched delayed neural networks with both stable and unstable subsystems is analyzed and several easy to verify conditions are derived to ensure the exponential mean square stability of switched delayed neural networks with stochastic disturbances. The effectiveness of the proposed results is illustrated by two simulation examples.

MSC:
93E15 Stochastic stability in control theory
92B20 Neural networks for/in biological studies, artificial life and related topics
93D20 Asymptotic stability in control theory
90B15 Stochastic network models in operations research
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