带有变化分布时滞的复值神经网络Lagrange稳定性  

Lagrangian Stability of Complex-Valued Neural Networks With Distributed Time-Varying Delays

作　　者：张磊[1] 宋乾坤[2] ZHANG Lei SONG Qian-kun(Department of Basic, Sichuan Engineering Technical College, Deyang , Sichuan 518000, P.R. China Department of Mathematics, Chongqing Jiaotong University, Chongqing 400074, P.R. China） （Contributed by SONG Qian-kun, M. AMM Editorial Board)

机构地区：[1]四川工程职业技术学院基础教学部,四川德阳618000 [2]重庆交通大学数学系,重庆400074

出　　处：《应用数学和力学》2017年第10期1180-1186,共7页Applied Mathematics and Mechanics

基　　金：国家自然科学基金(61773004);重庆高校创新团队建设计划(CXTDX201601022)~~

摘　　要：研究了带有变化分布时滞的复值神经网络Lagrange稳定性问题.通过构造合适的Lyapunov-Krasovskii泛函,并使用矩阵不等式技巧,建立了网络全局指数Lagrange稳定性的判定条件.提供的判据是复值线性矩阵不等式,能够使用MATLAB软件的YALMIP工具箱快速计算.The Lagrangian stability of complex-valued neural networks with distributed time-varying delays was investigated. By means of the Lyapunov-Krasovskii functional and the matrix inequality techniques,a delay-dependent sufficient condition was obtained to ensure the global exponential stability in a Lagrangian sense for the considered neural networks. The condition is expressed in the form of complex-valued linear matrix inequality,which can be checked numerically with the effective YALMIP toolbox in MATLAB.

关 键 词：复值神经网络 变化分布时滞 LAGRANGE稳定性 复值线性矩阵不等式 

分 类 号：O175.13[理学—数学]