非线性随机时滞系统的稳定性与应用

首先考虑了不确定性的一族非线笥随机时滞系统，建立了这种系统的均方指数稳定与几乎必须指数稳定的充分准则，其准则是时滞无关的，然后应用这些充分条件到一类不确定的随机时滞神经网络，得到了这咱神经网络指数稳定的产用判据。本文的结果是最近文献中某些结果的推广，最后一个数值例子说明的所给准则的有效性。

The Stability of Nonlinear Stochastic Delay Systems with Its Applications

In the first part of this paper we consider a family of nonlinear stochastic delay systems with uncertainties. For such systems, we establish sufficient criteria for the exponential stability in mean square and the almost sure exponential stability. These criteria are independent of delay. In the second part, we apply these sufficient conditions to a class of stochastic delay neural networks with uncertainties and obtain practical criteria to test exponential stability of these stochastic delay neural networks. Our results are generalizations of some recent ones reported in the literature. In final, a numerical example is given to illustrate the effectiveness of the obtained criteria.