基于改进自由权矩阵方法的神经网络时滞相关稳定性分析

Further Improvement of Free-weighting Matrix Approach for the Stability Analysis of Neural Networks with Time-varying Delay

针对具有不确定参数的时变时滞神经网络系统,利用改进的自由权矩阵方法,研究其时滞相关稳定性问题。通过考虑时变时滞及其上界和它们的差三者之间关系,同时保留Lyapunov-Krasovskii泛函导数中的有用项,得到具有更低保守性的基于线性矩阵不等式的神经网络系统时滞相关渐近稳定的充分条件。最后,数值例子表明该方法的有效性。

This paper investigates the stability problem of uncertain neural networks with time- varying delay by employing a further improved fre.e- weighting matrix approach, The relationship among the time - varying delay, its upper bound and their difference is taken into account. As a result, an less conservative LMI - based delay - dependent asymptotic stability criterion is obtained without ignoring any useful terms in the derivative of Lyapunov- Krasovskii functional. Finally, numerical examples are given to demonstrate the effectiveness and the merits of the proposed methods.