Journal of Applied Mathematics
Volume 2013 (2013), Article ID 710741, 10 pages
Research Article

Piecewise Convex Technique for the Stability Analysis of Delayed Neural Network

1College of Computer Science and Information, Guizhou University, Guiyang 550025, China
2School of Mathematics and Statistics, Guizhou University of Finance and Economics, Guiyang 550004, China
3College of Science, Guizhou University, Guiyang 550025, China

Received 12 May 2013; Accepted 2 July 2013

Academic Editor: Chong Lin

Copyright © 2013 Zixin Liu 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.


On the basis of the fact that the neuron activation function is sector bounded, this paper transforms the researched original delayed neural network into a linear uncertain system. Combined with delay partitioning technique, by using the convex combination between decomposed time delay and positive matrix, this paper constructs a novel Lyapunov function to derive new less conservative stability criteria. The benefit of the method used in this paper is that it can utilize more information on slope of the activations and time delays. To illustrate the effectiveness of the new established stable criteria, one numerical example and an application example are proposed to compare with some recent results.