Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (8): 36-38.DOI: 10.3778/j.issn.1002-8331.2009.08.011

• 研究、探讨 • Previous Articles     Next Articles

Robust stability of uncertain BAM neural networks with time-varying delays

FENG Wei1,2,WU Hai-xia2,ZHANG Wei2   

  1. 1.College of Automation,Chongqing University,Chongqing 400030,China
    2.Department of Computer and Modern Education Technology,Chongqing Education College,Chongqing 400067,China
  • Received:2008-09-01 Revised:2008-10-21 Online:2009-03-11 Published:2009-03-11
  • Contact: FENG Wei

不确定时滞BAM神经网络的鲁棒稳定性

冯 伟1,2,吴海霞2,张 伟2   

  1. 1.重庆大学 自动化学院,重庆 400030
    2.重庆教育学院 计算机与现代教育技术系,重庆 400067
  • 通讯作者: 冯 伟

Abstract: By free-weighting matrices and combining the method of inequality analysis,the problem of robust stability of a class of uncertain BAM neural networks with time-varying delays is investigated.Based on Lyapunov-Krasovskii functional,some new stability criteria are presented in terms of Linear Matrix Inequalities(LMIs) to guarantee the delayed BAM neural networks to be robustly stable for all admissible uncertainties.A numerical example is given to demonstrate the usefulness of the proposed robust stability criteria.

Key words: robust stability, uncertain Bidirectional Associative Memory(BAM) neural networks, time-varying delays, Linear Matrix Inequalities(LMIs)

摘要: 利用自由权值矩阵和不等式分析技巧,研究了一类不确定时滞BAM神经网络的鲁棒稳定性问题。通过构造适当的Lyapunov泛函,对于所有允许的不确定性,以线性矩阵不等式形式给出了时滞BAM神经网络的全局鲁棒稳定性判据,该判据能够利用Matlab的LMI工具箱很容易地进行检验。此外,仿真示例进一步证明了判据的有效性。

关键词: 鲁棒稳定性, 不确定双向联想记忆神经网络, 变时滞, 线性矩阵不等式