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Abstract and Applied Analysis
Volume 2014, Article ID 842976, 15 pages
Research Article

Robust Exponential Stabilization of Stochastic Delay Interval Recurrent Neural Networks with Distributed Parameters and Markovian Jumping by Using Periodically Intermittent Control

1College of Mathematics and Statistics, South Central University for Nationalities, Wuhan 430074, China
2School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China
3College of Automation, Huazhong University of Science and Technology, Wuhan 430074, China
4College of Science, Huazhong Agriculture University, Wuhan 430070, China

Received 13 January 2014; Accepted 14 February 2014; Published 27 April 2014

Academic Editor: Zhengguang Wu

Copyright © 2014 Junhao Hu 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.


We consider a class of stochastic delay recurrent neural networks with distributed parameters and Markovian jumping. It is assumed that the coefficients in these neural networks belong to the interval matrices. Several sufficient conditions ensuring robust exponential stabilization are derived by using periodically intermittent control and Lyapunov functional. The obtained results are very easy to verify and implement, and improve the existing results. Finally, an example with numerical simulations is given to illustrate the presented criteria.