Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (24): 15-18.DOI: 10.3778/j.issn.1002-8331.2010.24.005

• 博士论坛 • Previous Articles     Next Articles

Existence and stability of periodic solution for BAM neural networks

WANG Fen1,2,WU Huai-yu1   

  1. 1.College of Information Science and Engineering,Wuhan University of Science and Technology,Wuhan 430081,China
    2.College of Science,Wuhan University of Science and Technology,Wuhan 430081,China
  • Received:2010-03-23 Revised:2010-07-05 Online:2010-08-21 Published:2010-08-21
  • Contact: WANG Fen

BAM神经网络周期解的存在性与稳定性

王 芬1,2,吴怀宇1   

  1. 1.武汉科技大学 信息科学与工程学院,武汉 430081
    2.武汉科技大学 理学院,武汉 430081
  • 通讯作者: 王 芬

Abstract: By using the fixed point theorem and constructing suitable Lyapunov function,some sufficient conditions are obtained ensuring existence,uniqueness,and global exponential stability of periodic solution for BAM neural networks with time-varying delays.The obtained sufficient criteria are derived in terms of Linear Matrix Inequalities(LMIs),which can be easily checked by Matlab.An example is given to show the effectiveness of the obtained results.

Key words: neural networks, global exponential stability, delay, Lyapunov function

摘要: 利用不动点理论、Lyapunov泛函,研究了具变时滞的BAM神经网络周期解的存在性、唯一性和全局指数稳定性问题。所得的充分判别标准由线性矩阵不等式所表示,可以较容易地由Matlab进行验证。仿真实例表明,得到的判据是有效的。

关键词: 神经网络, 全局指数稳定性, 时滞, Lyapunov泛函

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