Novel global exponential stability analysis for BAM neural networks with time-varying delays

Authors:
Yonggang Chen;Shoujia Huang;Jingben Yin;Qingbo Li
Affiliations:
Department of Mathematics, Henan Institute of Science and Technology, Xinxiang, China;Department of Mathematics and Information Science, Zhengzhou University of Light Industry, Zhengzhou, China;Department of Mathematics, Henan Institute of Science and Technology, Xinxiang, China;Department of Mathematics and Information Science, Zhengzhou University of Light Industry, Zhengzhou, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

Citing 2
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Abstract

This paper considers the global exponential stability problem for a class of bidirectional associative memory (BAM) neural networks time-varying delays. By employing Lyapunov functional method and resorting to the less conservative technique for estimating the derivative of Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequalities (LMIs). Numerical example is presented to illustrate the less conservativeness of the obtained result.