本文通过构造新型的Lyapunov-Krasosvskii函数并利用矩阵不等式技巧获得了一类变时滞中立型BAM神经网络的全局稳定性判据,该判据便于应用.数值例子表明,与已有结果相比,该判据具有较低的保守性.
In this paper, by constructing a new Lyapunov-Krasovskii function and combining with the technique of the matrix inequality, we analyze the global stability for neutral bidirectional associative memory neural networks with time-varying delays. These criteria are easy to apply. Numerical examples show that the proposed method is less conservative than the previous ones.