研究一类带有时变时滞的中立型神经网络的全局指数稳定 性问题. 通过构造Lyapunov-Krasovskii 泛函并使用线性矩阵不等式方法, 建立了保障时滞神经网络全局指数稳定的新的时滞相关充分条件. 这些条 件用线性矩阵不等式表达. 进一步, 文章对一类不确定时滞中立型神经网络 给出了鲁棒全局指数稳定的新判据.

The paper is concerned with global exponential stability for a class of neutral-type neural networks with time-varying delays. By constructing an appro- riate Lyapunov-Krasovkii functional and with the help of linear matrix inequality (LMI) approaches, some delay-dependent sufficient conditions to guarantee the glob- ally exponential stability of such systems are established in terms of the linear matrix inequality (LMI). Furthermore, some novel criteria of robust globally exponential stability for a class of uncertain time-delay neutral-type neural networks are given.