Journal of Applied Mathematics
Volume 2008 (2008), Article ID 453627, 18 pages
Research Article

Periodic Oscillation of Fuzzy Cohen-Grossberg Neural Networks with Distributed Delay and Variable Coefficients

Hongjun Xiang1,2 and Jinde Cao1

1Department of Mathematics, Southeast University, Nanjing 210096, China
2Department of Mathematics, Xiangnan University, Chenzhou 423000, China

Received 4 July 2007; Accepted 6 December 2007

Academic Editor: George Jaiani

Copyright © 2008 Hongjun Xiang and Jinde Cao. 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 fuzzy Cohen-Grossberg neural networks with distributed delay and variable coefficients is discussed. It is neither employing coincidence degree theory nor constructing Lyapunov functionals, instead, by applying matrix theory and inequality analysis, some sufficient conditions are obtained to ensure the existence, uniqueness, global attractivity and global exponential stability of the periodic solution for the fuzzy Cohen-Grossberg neural networks. The method is very concise and practical. Moreover, two examples are posed to illustrate the effectiveness of our results.