Volume 7 Issue 2
Apr.  2017
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Jin-Liang Shao, Ting-Zhu Huang. Global Exponential Stability Analysis of a Class of Dynamical Neural Networks[J]. Journal of Electronic Science and Technology, 2009, 7(2): 171-174.
Citation: Jin-Liang Shao, Ting-Zhu Huang. Global Exponential Stability Analysis of a Class of Dynamical Neural Networks[J]. Journal of Electronic Science and Technology, 2009, 7(2): 171-174.

Global Exponential Stability Analysis of a Class of Dynamical Neural Networks

Funds:

This work was supported by Sichuan Province Foundation for Applied Basic Research and Leaders of Science and Technology under Grant No. 05JY029-068-2.

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  • Author Bio:

    Jin-Liang Shao research interests include robust control, neural network, and matrix analysis, jinliangshao@126.com;
    Ting-Zhu Huang, tzhuang@uestc.edu.cn

    Jin-Liang Shao research interests include robust control, neural network, and matrix analysis, jinliangshao@126.com;
    Ting-Zhu Huang, tzhuang@uestc.edu.cn

  • Received Date: 2008-01-15
  • Rev Recd Date: 2008-04-09
  • Publish Date: 2009-06-25

通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

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Global Exponential Stability Analysis of a Class of Dynamical Neural Networks

Funds:

This work was supported by Sichuan Province Foundation for Applied Basic Research and Leaders of Science and Technology under Grant No. 05JY029-068-2.

  • Author Bio:

Abstract: The problem of the global exponential stability of a class of Hopfield neural networks is considered. Based on nonnegative matrix theory, a sufficient condition for the existence, uniqueness and global exponential stability of the equilibrium point is presented. And the upper bound for the degree of exponential stability is given. Moreover, a simulation is given to show the effectiveness of the result.

Jin-Liang Shao, Ting-Zhu Huang. Global Exponential Stability Analysis of a Class of Dynamical Neural Networks[J]. Journal of Electronic Science and Technology, 2009, 7(2): 171-174.
Citation: Jin-Liang Shao, Ting-Zhu Huang. Global Exponential Stability Analysis of a Class of Dynamical Neural Networks[J]. Journal of Electronic Science and Technology, 2009, 7(2): 171-174.

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