引用本文: | 徐瑞萍,高存臣,考永贵.转移概率一般不确知时滞Markov跳变神经网络的同步[J].控制理论与应用,2015,32(8):1032~1039.[点击复制] |
XU Rui-ping,GAO Cun-chen,KAO Yong-gui.Synchronization for Markov jump neural networks with generally uncertain transition rates[J].Control Theory and Technology,2015,32(8):1032~1039.[点击复制] |
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转移概率一般不确知时滞Markov跳变神经网络的同步 |
Synchronization for Markov jump neural networks with generally uncertain transition rates |
摘要点击 2657 全文点击 1715 投稿时间:2014-11-30 修订日期:2015-08-29 |
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DOI编号 10.7641/CTA.2015.41107 |
2015,32(8):1032-1039 |
中文关键词 同步 一般不确知转移概率 Markov跳变神经网络 Kronecker积 |
英文关键词 synchronization generally uncertain transition rates Markov jump neural networks Kronecker product |
基金项目 国家自然科学基金项目(60974025)资助. |
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中文摘要 |
研究了一类具有一般不确知转移概率的时滞Markov跳变神经网络的渐近同步问题. 此类系统跳变过程的 转移概率完全未知或者仅知道其估计值, 因而更具有一般性. 通过选择适当的Lyapunov-Krasovskii函数, 利用线性 矩阵不等式(LMIs)方法, 得到了系统均方渐近同步的充分条件. 最后, 数值例子说明了所给结果的有效性. |
英文摘要 |
This paper investigates the asymptotical synchronization problem for a class of Markov jump neural networks (MJNNs) with generally uncertain transition rates (GUTRs). In the GUTR neural network model, each transition rate may be completely unknown or only its estimate value is known. This new uncertain model could be applied in many practical cases. Based on the Lyapunov-Krasovskii function method, a sufficient condition for the asymptotical synchronization in mean square is derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to illustrate the effectiveness of the developed method. |