Discrete Dynamics in Nature and Society
Volume 2008 (2008), Article ID 421614, 14 pages
doi:10.1155/2008/421614
Delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays
Yonggang Chen1
, Weiping Bi2
and Yuanyuan Wu3
1Department of Mathematics, Henan Institute of Science and Technology, Xinxiang 453003, China
2College of Mathematics and Information Science, Henan Normal University, Xinxiang 453007, China
3Key Laboratory of Measurement and Control of Complex Systems of Engineering, Ministry of Education, School of Automation, Southeast University, Nanjing 210096, China
Abstract
This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI). Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.