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Journal of Applied Mathematics
Volume 2014 (2014), Article ID 510358, 9 pages
Research Article

Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method

1Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing, 210044, China
2School of Economics & Management, Nanjing University of Information Science & Technology, Nanjing 210044, China

Received 29 September 2013; Revised 21 January 2014; Accepted 6 February 2014; Published 31 March 2014

Academic Editor: Naseer Shahzad

Copyright © 2014 Tianxiang Yao and Xianghong Lai. 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 work addresses the stability study for stochastic cellular neural networks with time-varying delays. By utilizing the new research technique of the fixed point theory, we find some new and concise sufficient conditions ensuring the existence and uniqueness as well as mean-square global exponential stability of the solution. The presented algebraic stability criteria are easily checked and do not require the differentiability of delays. The paper is finally ended with an example to show the effectiveness of the obtained results.