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Journal of Applied Mathematics
Volume 2012, Article ID 829594, 12 pages
http://dx.doi.org/10.1155/2012/829594
Research Article

Robust Stochastic Stability Analysis for Uncertain Neutral-Type Delayed Neural Networks Driven by Wiener Process

1College of Information Science and Engineering, Ocean University of China, Qingdao 266100, China
2Department of Mathematics, Ocean University of China, Qingdao 266100, China

Received 9 July 2011; Revised 20 September 2011; Accepted 27 September 2011

Academic Editor: Shiping Lu

Copyright © 2012 Weiwei Zhang and Linshan Wang. 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.

Abstract

The robust stochastic stability for a class of uncertain neutral-type delayed neural networks driven by Wiener process is investigated. By utilizing the Lyapunov-Krasovskii functional and inequality technique, some sufficient criteria are presented in terms of linear matrix inequality (LMI) to ensure the stability of the system. A numerical example is given to illustrate the applicability of the result.