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Mathematical Problems in Engineering
Volume 2015, Article ID 717513, 11 pages
Research Article

Global Asymptotic Stability of Switched Neural Networks with Delays

1College of Electrical and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China
2College of Science, Huazhong Agricultural University, Wuhan 430070, China

Received 1 September 2015; Accepted 30 November 2015

Academic Editor: Yuan Fan

Copyright © 2015 Zhenyu Lu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper investigates the global asymptotic stability of a class of switched neural networks with delays. Several new criteria ensuring global asymptotic stability in terms of linear matrix inequalities (LMIs) are obtained via Lyapunov-Krasovskii functional. And here, we adopt the quadratic convex approach, which is different from the linear and reciprocal convex combinations that are extensively used in recent literature. In addition, the proposed results here are very easy to be verified and complemented. Finally, a numerical example is provided to illustrate the effectiveness of the results.