分布时滞模糊Hopfield神经网络周期解的指数稳定性  

Exponential Stability of Periodic Solutions in Fuzzy Hopfield Neural Networks with Distributed Delays

作　　者：符素云[1] 陈立平[1] 吴然超[1] 

机构地区：[1]安徽大学数学科学学院,安徽合肥230039

出　　处：《黄山学院学报》2009年第5期7-9,共3页Journal of Huangshan University

基　　金：安徽省自然科学基金资助(070416225);安徽省教育厅自然科学基金重点资助(KJ2007A003;KJ2008A025)

摘　　要：对一类具有分布时滞的Hopfield模糊神经网络模型,在假设激励函数是全局Lipschitz连续的条件下,应用Lyapunov稳定性理论等分析的方法,研究了此类模型周期解的存在性与指数稳定性,得到了唯一周期解存在与指数稳定的充分条件,并举实例说明它的有效性。In this paper, a type of fuzzy Hopfield neural network （FHNN） with distributed delays is discussed. Based on the supposition that excitation functions are Lipschitz continuous functions, sufficient conditions for the existence and the exponential stability of periodic solutions are obtained by using analytic methods such as the stability of Lyapunov. An illustrative example is given to demonstrate the effectiveness of the obtained results.

关 键 词：模糊HOPFIELD神经网络 分布时滞 周期解 指数稳定性 

分 类 号：O175.1[理学—数学]