Exponential Stability in Mean Square for Stochastic Hopfield Delay Neural Networks: an LMI Approach
随机Hopfield时滞神经网络均方指数稳定性: LMI方法

By using a technique of model transformation of the system, a new type of Lyapunov functional is introduced. By applying this new Lyapunov functional, a novel delay-dependent sufficient condition of exponential stability in mean square for stochastic Hopfield delay neural networks is derived in terms of linear matrix inequalities (LMIs). A delay-independent sufficient condition is also presented. Numerical examples show that the proposed method is less conservative than the previous ones.