具有离散与分布时滞神经网络鲁棒稳定性

Robust stability for a class of neural network with discrete and distributed delays

针对一类具有离散与分布时滞的神经网络存在的鲁棒稳定性问题,考虑时滞与参数扰动等不确定因素,通过加入三重积分条件,构造合理的Lyapunov-Krasovskii泛函,并采用线性矩阵不等式技术.研究结果表明:得到系统全局指数鲁棒稳定的时滞相关充分条件,同时能够得到系统全局渐进鲁棒稳定的充分条件,表明了该方法的有效性和可行性.

The main purpose of this paper is to study the robust stability problem for a class of neural network with discrete and distributed delays in parameter uncertainty. By constructing appropriate Lyapunov-Krasovskii functionals involving triple terms, this paper derived several stability criteria for the delayed neural networks in terms of LMIs. The result shows the validity and feasibility of the proposed criteria.