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本文研究了一类随机时滞递归神经网络的指数稳定性问题.利用非负鞅收敛定理和Lyapunov泛函的方法,获得了这类神经网络矩指数稳定性的新的代数准则,所给代数准则简单易用.一个具体实例用来说明稳定性判别准则的应用.
In this paper, we study the exponential stability of a class of recurrent neural networks with stochastic delays. By using the nonnegative martingale convergence theorem and the Lyapunov functional, we obtain the new algebraic criteria for the moment exponential stability of such neural networks. Simple and easy to use. A concrete example is used to illustrate the application of stability criteria.