首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于时滞分割技术的时滞神经网络系统时滞相依全局稳定性分析
引用本文:毛凯,孙校书,杨树杰,刘丹.基于时滞分割技术的时滞神经网络系统时滞相依全局稳定性分析[J].海军航空工程学院学报,2019,34(2):239-244.
作者姓名:毛凯  孙校书  杨树杰  刘丹
作者单位:海军航空大学,山东烟台,264001;海军航空大学,山东烟台,264001;海军航空大学,山东烟台,264001;海军航空大学,山东烟台,264001
摘    要:通过构造一个新的增广 Lyapunov-Krasovskii泛函,利用时滞分割技术并结合自由权矩阵、Jensen积分不等式,得到一个时滞神经网络系统时滞相依全局渐近稳定新判据。该判据以 LMI的形式给出,便于计算和验证。数值实例表明,文章结果改进了相关文献结论,具有更低的保守性。

关 键 词:时滞神经网络系统(DNN)  全局渐近稳定  时滞分割技术  自由权矩阵  Jensen积分不等式

Delay-Dependent Global Stability of Neural Networks With Time Delay Based on Delay
MAO Kai,SUN Xiaoshu,YANG Shujie and LIU Dan.Delay-Dependent Global Stability of Neural Networks With Time Delay Based on Delay[J].Journal of Naval Aeronautical Engineering Institute,2019,34(2):239-244.
Authors:MAO Kai  SUN Xiaoshu  YANG Shujie and LIU Dan
Institution:Naval Aviation University, Yantai Shandong 264001, China,Naval Aviation University, Yantai Shandong 264001, China,Naval Aviation University, Yantai Shandong 264001, China and Naval Aviation University, Yantai Shandong 264001, China
Abstract:In this paper, a delay-dependent stability sufficient condition was obtained by a newly constructed Lyapunov-Krasovskii functional together with delay fractioning technique, free weighing matrix method and Jensen integral inequali.ty, which was in form of LMIs and was less conservative than the existing ones.
Keywords:time-delay neural networks (DNN)  global asymptotically stability  delay fractioning technique  free weightingmatrix  Jensen integral inequality
本文献已被 万方数据 等数据库收录!
点击此处可从《海军航空工程学院学报》浏览原始摘要信息
点击此处可从《海军航空工程学院学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号