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Abstract and Applied Analysis
Volume 2012 (2012), Article ID 358362, 14 pages
Research Article

Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time-Varying Delays

1College of Science, Guilin University of Technology, Guangxi, Guilin 541004, China
2Guizhou Key Laboratory of Economics System, Guizhou College of Finance and Economics, Guizhou, Guiyang 550004, China

Received 12 January 2012; Accepted 26 February 2012

Academic Editor: Josef Diblík

Copyright © 2012 Yuanfu Shao 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.


By using Schaeffer's theorem and Lyapunov functional, sufficient conditions of the existence and globally exponential stability of positive periodic solution to an impulsive neural network with time-varying delays are established. Applications, examples, and numerical analysis are given to illustrate the effectiveness of the main results.