具有混合时滞的随机神经网络的无源性分析

Passivity Analysis for Stochastic Neural networks With Mixed Delays

针对一类具有混合时滞的随机神经网络,研究其无源性分析问题.假设神经网络的离散状态时滞是不确定的,看成一个标称值受时变扰动;神经网络的分布式状态时滞是定常的.通过构造适当的离散化Lyapunov-Krasovskii泛函,并结合自由权矩阵方法,以线性矩阵不等式的形式给出了保证具有混合时滞的随机神经网络无源的时滞依赖充分条件.

This paper is concerned with the problem of passivity analysis for stochastic neural networks with mixed delays.It is assumed that the discrete delay is uncertain and seen as a composition of a nominal value subject to a time varying perturbation.The distributed delay is supposed to be constant.By constructing a appropriate discretized Lyapunov-Krasovskii functional and utilizing free-weight matrix techniques,delay-dependent passivity criteria are established in terms of linear matrix inequalities to guarantee the passivity per-formance of the addressed neural networks.