| 刘自鑫,吕恕,钟守铭,叶茂.离散神经网络指数稳定的增强李亚普诺夫方法[J].数学研究及应用,2011,31(3):479~489 |
| 离散神经网络指数稳定的增强李亚普诺夫方法 |
| Augmented Lyapunov Approach to Exponential Stability of Discrete-Time Neural Networks |
| 投稿时间：2009-03-30 修订日期：2010-04-26 |
| DOI：10.3770/j.issn:1000-341X.2011.03.013 |
| 中文关键词: 离散神经网络 鲁棒指数稳定 时滞依赖准则 时变时滞. |
| 英文关键词:discrete-time neural networks robust exponential stability delay-dependent criterion time-varying delay. |
| 基金项目:贵州省科学技术基金(Grant No.[2010]2139); 教育部新世纪优秀人才计划(Grant No.NCET-06-0811). |
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| 中文摘要: |
| 研究了一类变时滞不定离散神经网络鲁棒指数稳定问题. 结合线性矩阵不等式技术,通过构造一个新的增强李亚普诺夫函数, 得到了新的指数稳定判据. 与最近文献中的结果相比, 新判据的保守性显著降低. 两个数值算例表明了新判据的较弱保守性及有效性. |
| 英文摘要: |
| This paper addresses the problem of robust stability for a class of discrete-time neural networks with time-varying delay and parameter uncertainties. By constructing a new augmented Lyapunov-Krasovskii function, some new improved stability criteria are obtained in forms of linear matrix inequality (LMI) technique. Compared with some recent results in the literature, the conservatism of these new criteria is reduced notably. Two numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results. |
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