Journal
IET CONTROL THEORY AND APPLICATIONS
Volume 7, Issue 3, Pages 354-362Publisher
INST ENGINEERING TECHNOLOGY-IET
DOI: 10.1049/iet-cta.2012.0585
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Funding
- National Natural Science Foundation of China [61174085, 61074025, 60834002]
- National High Technology Research and Development Programme of China (863 Programme) [2009AA012201]
- Ph. D. Programs Foundation of Ministry of Education of China [2012AA062105]
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This article studies the problem of stability analysis for neural networks (NNs) with two additive time-varying delay components. By taking both the independence and the variation of the two delay components into consideration, a more general Lyapunov functional is defined. By estimating the upper bound of the derivative of the Lyapunov functional more tightly, a less conservative delay-dependent stability criterion is established in terms of linear matrix inequalities. To reduce the computational complexity, a method for eliminating slack variables is provided, and then a simplified stability criterion is obtained. Some numerical examples are given to illustrate the effectiveness of the proposed method and the significant improvement over the existing results.
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