摘要
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.
The exponential stability in mean square for a stochastic Cohen-Grossberg-type BAM neural network is discussed by constructing suitable Lyapunov function and using the Ito formula. The general sufficient conditions for the exponential stability in mean square are estabished. Finally an illustrative example is given to show the effectiveness of our results.
出处
《数学的实践与认识》
CSCD
北大核心
2012年第17期199-205,共7页
Mathematics in Practice and Theory
基金
浙江省自然科学基金(Y6100096
LQ12F02007)
绍兴文理学院重点资助项目(2011LG1001)
