Abstract and Applied Analysis
Volume 2012 (2012), Article ID 647231, 18 pages
Research Article

Global Robust Exponential Stability Analysis for Interval Neural Networks with Mixed Delays

Institute of Applied Mathematics, Shijiazhuang Mechanical Engineering College, Shijiazhuang 050003, China

Received 17 September 2012; Revised 21 November 2012; Accepted 21 November 2012

Academic Editor: Józef Banaś

Copyright © 2012 Yanke Du and Rui Xu. 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.


A class of interval neural networks with time-varying delays and distributed delays is investigated. By employing H-matrix and M-matrix theory, homeomorphism techniques, Lyapunov functional method, and linear matrix inequality approach, sufficient conditions for the existence, uniqueness, and global robust exponential stability of the equilibrium point to the neural networks are established and some previously published results are improved and generalized. Finally, some numerical examples are given to illustrate the effectiveness of the theoretical results.