一类随机时滞神经网络的全局渐进稳定性分析

Global asymptotic stability analysis of a class of stochastic delay neural networks

研究一类具变时滞与分布时滞的随机神经网络模型零解的全局渐进稳定性,该模型考虑了神经网络的随机扰动性。通过构造新型的Lyapunov泛函,结合不等式技巧,以线性矩阵不等式的形式,并给出了系统全局渐进稳定的充分条件。数值算例说明了结果的正确性。

Global asymptotic stability for the equilibrium solution of a class of stochastic neural networks with time-varying delays and distributed delay is considered.By constructing suitable Lyapunov functionals and combining with matrix inequality technique,a new simple sufficient condition is presented for the global asymptotic stability in the mean square senses of stochastic neural networks with time-varying delays and distributed delay.A numerical example demonstrates the usefulness of the new proposed global asymptotic stability criteria.