Synchronization of chaotic nonlinear continuous neural networks with time-varying delay
Synchronization of chaotic nonlinear continuous neural networks with time-varying delay
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DOI：
10.1007/s11571-011-9162-0
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发表时间：
2011-07
影响因子：
3.7
通讯作者：
P. Balasubramaniam;R. Chandran;S. Theesar
中科院分区：
文献类型：
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作者：
P. Balasubramaniam;R. Chandran;S. Theesar
研究了一类延迟连续时间非线性复杂神经网络的同步问题。考虑更一般的时变时滞情况，得到与时滞相关的状态反馈同步增益矩阵。利用李雅普诺夫稳定性理论，从线性矩阵不等式（lmi）的角度导出了充分的同步判据。通过将时滞区间分解为多个等距子区间，在这些区间上构造Lyapunov-Krasovskii泛函（lkf）。利用这些lkf，针对有时变延迟导数和无时变延迟导数两种情况，用lmi给出了新的时延相关同步准则。数值算例表明了该方法的有效性。
In this paper, the synchronization problem for delayed continuous time nonlinear complex neural networks is considered. The delay dependent state feed back synchronization gain matrix is obtained by considering more general case of time-varying delay. Using Lyapunov stability theory, the sufficient synchronization criteria are derived in terms of Linear Matrix Inequalities (LMIs). By decomposing the delay interval into multiple equidistant subintervals, Lyapunov-Krasovskii functionals (LKFs) are constructed on these intervals. Employing these LKFs, new delay dependent synchronization criteria are proposed in terms of LMIs for two cases with and without derivative of time-varying delay. Numerical examples are illustrated to show the effectiveness of the proposed method.