Stability analysis of impulsive stochastic Cohen–Grossberg neural networks driven by G-Brownian motion
Stability analysis of impulsive stochastic Cohen–Grossberg neural networks driven by G-Brownian motion
复制标题
G-布朗运动驱动的脉冲随机Cohen-Grossberg神经网络的稳定性分析
DOI：
10.1080/00207179.2017.1328745
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发表时间：
--
影响因子：
2.1
通讯作者：
Zhou Qing
中科院分区：
文献类型：
--
作者：
Ren Yong;Gu Yuanfang;Zhou Qing
研究了一类由YG-Brown运动驱动的脉冲随机Cohen-Grossberg神经网络的稳定性。利用G-Lyapunov函数、Borel-坎特利引理和不等式技巧，建立了关于一般衰减函数的矩稳定和拟确定稳定的一系列充分条件。最后给出了一个具体的算例来说明所得结果。
This paper is devoted to study the stability of a class of impulsive stochastic Cohen–Grossberg neural networks driven byG-Brownian motion. By means ofG-Lyapunov function, Borel–Cantelli lemma and inequality technique, a series of sufficient conditions onpth moment stability and quasi-sure stability with respect to a general decay function are established. A concrete example is given to illustrate the obtained results.