Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay

Wenguang Luo, Xiuling Wang, Yonghua Liu and Hongli Lan

Abstract and Applied Analysis, 2013, vol. 2013, 1-7

Abstract:

The problem of global exponential stability for recurrent neural networks with time-varying delay is investigated. By dividing the time delay interval [ ] into dynamical subintervals, a new Lyapunov-Krasovskii functional is introduced; then, a novel linear-matrix-inequality (LMI-) based delay-dependent exponential stability criterion is derived, which is less conservative than some previous literatures (Zhang et al., 2005; He et al., 2006; and Wu et al., 2008). An illustrate example is finally provided to show the effectiveness and the advantage of the proposed result.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:540951

DOI: 10.1155/2013/540951

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