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Globally exponential stability of neural networks with variable delays.IEEE Trans on Circuit Systems I

By Yan Zhang

Abstract

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

Topics: Neural Networks, Exponential Stability, Mixed Time-varying Delays, Lyapunov-Krasovskii Functional, Linear Matrix Inequality
Year: 2003
OAI identifier: oai:CiteSeerX.psu:10.1.1.412.2035
Provided by: CiteSeerX
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