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Abstract and Applied Analysis
Volume 2013 (2013), Article ID 631734, 9 pages
Research Article

Dynamical Behaviors of Stochastic Hopfield Neural Networks with Both Time-Varying and Continuously Distributed Delays

1Department of Mathematics, Zhaoqing University, Zhaoqing 526061, China
2School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China
3School of Mathematics and Physics, Wuhan Textile University, Wuhan 430073, China

Received 24 December 2012; Revised 19 March 2013; Accepted 20 March 2013

Academic Editor: Chuangxia Huang

Copyright © 2013 Qinghua Zhou 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.


This paper investigates dynamical behaviors of stochastic Hopfield neural networks with both time-varying and continuously distributed delays. By employing the Lyapunov functional theory and linear matrix inequality, some novel criteria on asymptotic stability, ultimate boundedness, and weak attractor are derived. Finally, an example is given to illustrate the correctness and effectiveness of our theoretical results.