一类含脉冲的随机区间细胞神经网络模型的周期解和稳定性  

Global Exponential Stability of Periodic Solution for a Class of Stochastic Interval Cellular Neural Networks with Impulsive Effects

作　　者：张伟伟[1] 王林山[2] 

机构地区：[1]中国海洋大学信息科学与工程学院,山东青岛266100 [2]中国海洋大学数学科学学院,山东青岛266100

出　　处：《中国海洋大学学报（自然科学版）》2012年第10期116-119,共4页Periodical of Ocean University of China

基　　金：国家自然科学基金项目(11171374);山东省自然科学基金重点项目(ZR2011AZ001)资助

摘　　要：讨论了一类含脉冲的S-分布时滞随机区间细胞神经网络的周期解和指数稳定性问题。利用随机分析的知识、不等式技巧和Poincaré压缩映像理论,研究了系统周期解的存在性和稳定性,得到了S-分布时滞随机细胞神经网络周期解的存在性和全局p阶指数稳定性的新代数判据,同时对周期解的指数收敛率进行了估计,最后通过例子说明了结果的实用性和有效性。In this paper, we consider the global exponential stability of periodic solution for a class of im-pulsive stochastic interval cellular neural networks with S-type distributed delays. By utilizing the sto-chastic analysis theory,inequality technique and Poincare contraction theory, we studied the existence and stability of the addressed system, and obtained some new sufficient conditions ensuring the existence of the periodic solutions and the exponential p-stability of the addressed system, the exponential convergence rate was estimated simultaneously. Finally, a numeric example was given to illustrate the effectiveness of our results.

关 键 词：区间细胞神经网络 随机 脉冲 S-分布时滞 周期解 

分 类 号：O175[理学—数学]