Discrete Dynamics in Nature and Society
Volume 2012 (2012), Article ID 435402, 21 pages
Research Article

Stability in Switched Cohen-Grossberg Neural Networks with Mixed Time Delays and Non-Lipschitz Activation Functions

1College of Science, Yanshan University, Qinhuangdao 066001, China
2College of Economics and Finance, Huaqiao University, Quanzhou 362021, China

Received 20 January 2012; Accepted 25 March 2012

Academic Editor: Piyapong Niamsup

Copyright © 2012 Huaiqin Wu 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.


The stability for the switched Cohen-Grossberg neural networks with mixed time delays and 𝛼 -inverse Hölder activation functions is investigated under the switching rule with the average dwell time property. By applying multiple Lyapunov-Krasovskii functional approach and linear matrix inequality (LMI) technique, a delay-dependent sufficient criterion is achieved to ensure such switched neural networks to be globally exponentially stable in terms of LMIs, and the exponential decay estimation is explicitly developed for the states too. Two illustrative examples are given to demonstrate the validity of the theoretical results.