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, issue 1

Abstract: The problem of global exponential stability for recurrent neural networks with time‐varying delay is investigated. By dividing the time delay interval [0, τ(t)] into K + 1 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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https://doi.org/10.1155/2013/540951

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Persistent link: https://EconPapers.repec.org/RePEc:wly:jnlaaa:v:2013:y:2013:i:1:n:540951

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