变时滞不确定性神经网络的鲁棒稳定性标准  

Robust stability criterion for uncertain neural network with time varying delays

作　　者：杨丽芸[1] 冯红侠[2] 仇计清[1] 杨洪玖[1] 

机构地区：[1]河北科技大学理学院,河北石家庄050018 [2]秦皇岛市抚宁县第二中学,河北秦皇岛066300

出　　处：《河北科技大学学报》2008年第1期63-68,共6页Journal of Hebei University of Science and Technology

摘　　要：研究了一类带变时滞和参数不确定的神经网络鲁棒稳定性问题。其中考虑的不确定性为范数有界不确定性,系统参数具有的这种不确定性是与时间相关的,但它的参数被限制在一定范围内,时间滞后函数是随时间变化而改变的,但它的导数是小于1的。并且通过一个线性矩阵不等式的方法得到一个充要条件,这个充要条件可以使带时滞的神经且有一个平衡点,并且在这个平衡点上具有鲁棒稳定性。这种基于线性矩阵不等式的充分条件可以通过近年发展的解线性矩阵不等式的算法得到数值结果,并通过数值例子说明了这个技术的有效性。This paper considers the problem of robust stability for uncertain neural networks with time varying delays. The uncertainties considered are norm-bounded uncertainties. These unceitainties of system parameters are associated with time, but the norm is restricted in a certain scope, the time delay function is improved with time, and its derivative is less than one. A linear matrix inequality （LMI） approach is developed to derive sufficient conditions ensuring the delayed neural network to have a equilibrium point, which is robustly stable. The proposed LMI conditions can be checked easily by recently developed algorithms. A numerical example is given to illustrate the effectiveness of the developed techniques.

关 键 词：神经网络 变时滞 鲁棒稳定性 线性矩阵不等式 范数有界参数不确定 

分 类 号：O635[理学—高分子化学]