基于马氏切换随机Cohen-Grossberg神经网络的自适应同步研究  

Adaptive synchronization for stochastic Cohen-Grossberg neural networks with Markovian switching

作　　者：马小康[1] 印凡成[1] 

机构地区：[1]河海大学理学院,南京211100

出　　处：《黑龙江大学自然科学学报》2017年第1期48-53,共6页Journal of Natural Science of Heilongjiang University

基　　金：中央高校科研业务费青年教师科研创新能力培育项目(2015B19814)

摘　　要：使用M矩阵方法,结合随机分析理论和自适应控制技术,讨论一类具有马尔可夫切换的随机时滞Cohen-Grossberg神经网络的自适应均方指数同步问题,获得保证误差系统指数稳定的充分条件。一个数值仿真例子验证了所得结论的正确性和有效性。By using M-matrix method combined with stochastic analysis theory and adaptive control technique, the adaptive mean square exponential synchronization for a class of stochastic delayed Cohen- Grossberg neural networks with Markovian switching is studied. Meanwhile, some sufficient conditions for the exponential stability of the error system are derived. A numerical simulation example is provided to examine the correctness and effectiveness of the obtained theoretic results .

关 键 词：自适应反馈控制 均方指数同步 随机神经网络 马尔可夫切换 M矩阵 

分 类 号：O175[理学—数学]