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Mathematical Problems in Engineering
Volume 2015, Article ID 341839, 10 pages
http://dx.doi.org/10.1155/2015/341839
Research Article

New Results on Passivity for Discrete-Time Stochastic Neural Networks with Time-Varying Delays

1School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, China
2School of Information Engineering, Fuyang Teachers College, Fuyang 236041, China
3School of Electrical and Information Technology, Yunnan Minzu University, Kunming 650500, China
4School of Business, Fuyang Teachers College, Fuyang 236041, China

Received 30 November 2014; Accepted 24 December 2014

Academic Editor: Yun-Bo Zhao

Copyright © 2015 Wei Kang 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.

Abstract

The problem of passivity analysis for discrete-time stochastic neural networks with time-varying delays is investigated in this paper. New delay-dependent passivity conditions are obtained in terms of linear matrix inequalities. Less conservative conditions are obtained by using integral inequalities to aid in the achievement of criteria ensuring the positiveness of the Lyapunov-Krasovskii functional. At last, numerical examples are given to show the effectiveness of the proposed method.