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Abstract and Applied Analysis
Volume 2013 (2013), Article ID 615947, 15 pages
Research Article

Sliding Intermittent Control for BAM Neural Networks with Delays

1Department of Mathematics, Research Center for Complex Systems and Network Sciences, Southeast University, Nanjing 210096, China
2Department of Engineering, Faculty of Engineering and Science, University of Agder, 4898 Grimstad, Norway
3Department of Mathematics, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Received 9 May 2013; Accepted 29 May 2013

Academic Editor: Zidong Wang

Copyright © 2013 Jianqiang 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.


This paper addresses the exponential stability problem for a class of delayed bidirectional associative memory (BAM) neural networks with delays. A sliding intermittent controller which takes the advantages of the periodically intermittent control idea and the impulsive control scheme is proposed and employed to the delayed BAM system. With the adjustable parameter taking different particular values, such a sliding intermittent control method can comprise several kinds of control schemes as special cases, such as the continuous feedback control, the impulsive control, the periodically intermittent control, and the semi-impulsive control. By using analysis techniques and the Lyapunov function methods, some sufficient criteria are derived for the closed-loop delayed BAM neural networks to be globally exponentially stable. Finally, two illustrative examples are given to show the effectiveness of the proposed control scheme and the obtained theoretical results.