具有变时滞的静态神经网络新的稳定性条件

New Stability Conditions of Static Neural Networks with Varying Delays

考虑一类具有变时滞的静态神经网络的渐近稳定性问题,基于Lyapunov稳定性理论,时滞分解的思想,并利用时滞导数的上下界,得到了线性矩阵不等式表示的新的渐近稳定性条件,最后,两个数值例子表明所得结果较一些现存结果具有更小的保守性。

This paper studys a class of varying delay of the static asymptotic stability of neural networks, based on Lyapunov stability theory, delaying the decomposition of thinking, and the use of delay, ng derivative upper and lower bounds, linear matrix inequality has been expressed in new asymptotic stability condition, and finally the results of two numerical examples show the results compared with some existing smaller conservative.