Exponential Stability for Neural Networks with Mixed Time Delays under State-dependent Switching ?
نویسنده
چکیده
In this paper, the switched generalized neural networks with mixed time-varying delays are proposed. Based on the strictly complete property of the matrices system, a switching rule which depends on the state of the network is designed. By employing a novel Lyapunov-Krasovskii functional, a delaydependent criterion is achieved in terms of Linear matrix inequalities (LMIs) which guarantees the exponential stability for such switched neural networks. A numerical example is given to illustrate the effectiveness of the theoretical results.
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