Estimation of exponential convergence rate and exponential stability for neural networks with time-varying delay

Fenghua Tu and Xiaofeng Liao

Chaos, Solitons & Fractals, 2005, vol. 26, issue 5, 1499-1505

Abstract: We study the problem of estimating the exponential convergence rate and exponential stability for neural networks with time-varying delay. Some criteria for exponential stability are derived by using the linear matrix inequality (LMI) approach. They are less conservative than the existing ones. Some analytical methods are employed to investigate the bounds on the interconnection matrix and activation functions so that the systems are exponentially stable.

Date: 2005
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:26:y:2005:i:5:p:1499-1505

DOI: 10.1016/j.chaos.2005.04.014

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