标题:
时滞忆阻神经网络的Lagrange稳定性Lagrange Stability of Memristive Recurrent Neural Networks with Delays
作者:
殷芳霞, 李小林
关键字:
Lagrange稳定, 非光滑分析, 线性矩阵不等式Lagrange Stability, Nonsmooth Analysis, Linear Matrix Inequality (LMI)
期刊名称:
《Pure Mathematics》, Vol.6 No.3, 2016-05-30
摘要:
在本文中我们研究了时滞递归忆阻神经网络在Lagrange意义下的全局指数稳定性。通过运用非光滑分析方法、微分包含和不等式技巧[1] [2]，我们得到了新的忆阻神经网络Lagrange稳定的充分条件，同时，我们给出了全局吸引集的估计方法。
In this paper, we study the globally exponential stability in a Lagrange sense for memristive re-current neural networks with time-varying delays. By the results from the theories of nonsmooth analysis, differential inclusions and linear matrix inequalities [1] [2], a novel sufficient criterion in the form of linear matrix inequality is given to confirm the Lagrange stability of memristive re-current neural networks. Meanwhile, the estimation of the globally exponentially attractive set is also given.