Global robust stability of complex-valued recurrent neural networks with time-delays and uncertainties

作     者：Wei Zhang Chuandong Li Tingwen Huang 

作者机构：College of Computer Science Chongqing UniversityChongqing 400044 P. R. China Department of MathematicsTexas A &M University at Qatar Qatar 

出 版 物：《International Journal of Biomathematics》 (生物数学学报（英文版）)

年 卷 期：2014年第7卷第2期

页      面：79-102页

核心收录：

学科分类：0711[理学-系统科学] 12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 0835[工学-软件工程] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 071102[理学-系统分析与集成] 081103[工学-系统工程] 

基　　金：This publication was made possible by NPRP Grant ≠NPRP 4-1162-1-181 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. This work was also supported by Natural Science Foundation of China (Grant No. 61374078) 

主　　题：Gomplex-valued recurrent neural networks robust stability global asymp-totical stability. 

摘      要：This paper focuses on the existence, uniqueness and global robust stability of equilibrium point for complex-valued recurrent neural networks with multiple time-delays and under parameter uncertainties with respect to two activation functions. Two sufficient conditions for robust stability of the considered neural networks are presented and established in two new time-independent relationships between the network parameters of the neural system, Finally, three illustrative examples are given to demonstrate the theoretical results.