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通过构造Lyapunov函数,利用随机微分的Ito公式,研究了一类含有时滞的随机Cohen-Grossberg-type BAM神经网络的均方指数稳定性,并给出判定的条件,最后举例子说明结果的正确性.
By constructing Lyapunov function and stochastic differential Ito formula, we study the mean square exponential stability of a class of stochastic Cohen-Grossberg-type BAM neural networks with delay and give the conditions for the decision. Finally, an example is given to illustrate the correctness of the results Sex.