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Discrete Dynamics in Nature and Society
Volume 2007, Article ID 67675, 9 pages
Research Article

On Global Exponential Stability of Discrete-Time Hopfield Neural Networks with Variable Delays

1Liaoning Key Lab of Intelligent Information Processing, Dalian University, Dalian 116622, China
2Department of Computer Science, Peking University, Beijing 100871, China

Received 1 December 2006; Revised 4 February 2007; Accepted 12 March 2007

Copyright © 2007 Qiang Zhang 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.


Global exponential stability of a class of discrete-time Hopfield neural networks with variable delays is considered. By making use of a difference inequality, a new global exponential stability result is provided. The result only requires the delay to be bounded. For this reason, the result is milder than those presented in the earlier references. Furthermore, two examples are given to show the efficiency of our result.