New conditions for global exponential stability of continuous-time neural networks with delays

被引：9
|
作者：
Gao, Haibo [1 ]
Song, Xingguo [1 ]
Ding, Liang [1 ]
Liu, Deyou [2 ]
Hao, Minghui [1 ]
机构：
[1] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150001, Peoples R China
[2] Yanshan Univ, Qinhuangdao 066004, Peoples R China
来源：
NEURAL COMPUTING & APPLICATIONS | 2013年 / 22卷 / 01期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Global exponential stability (GES); Homeomorphism; Equilibrium point; Neural network (NN); Lyapunov functional; ASYMPTOTIC STABILITY; ABSOLUTE STABILITY;
D O I：
10.1007/s00521-011-0745-9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we investigate the global exponential stability of delayed neural network systems. For this purpose, the activation functions are assumed to be globally Lipschitz continuous. The properties of norms and the relationship of homeomorphism are adjusted to ensure the existence as well as the uniqueness of the equilibrium point. Then by employing suitable Lyapunov functional, some delay-independent sufficient conditions are derived for exponential convergence toward global equilibrium state associated with different input sources. The obtained results are shown to be more general and less restrictive than the previous results derived in the literature. Lastly, a number of examples are provided to demonstrate the validity of the results proposed.
引用
收藏
页码：41 / 48
页数：8
相关论文
共 50 条
  • [41] Global Exponential Stability for Complex-Valued Recurrent Neural Networks With Asynchronous Time Delays
    Liu, Xiwei
    Chen, Tianping
    IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2016, 27 (03) : 593 - 606
  • [42] Global Exponential Stability for Impulsive Neural Networks With Discrete and Distributed Time-varying Delays
    Wu, Liang
    Zhao, Lei
    Zhao, Yingfeng
    Ma, Baolin
    PROCEEDINGS OF 2010 INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND INDUSTRIAL ENGINEERING, VOLS I AND II, 2010, : 660 - 664
  • [43] NEW CRITERIA OF EXPONENTIAL STABILITY FOR BAM NEURAL NETWORKS WITH DELAYS
    Wang Jinhua Xiang Hongjun(Dept.of Math.
    Annals of Differential Equations, 2007, (02) : 209 - 217
  • [44] New global exponential stability result to a general Cohen–Grossberg neural networks with multiple delays
    Zhengqiu Zhang
    Taipo Zhang
    Shengye Huang
    Ping Xiao
    Nonlinear Dynamics, 2012, 67 : 2419 - 2432
  • [45] Global Exponential Stability of Cohen-Grossberg Neural Network with Time Varying Delays
    Zhang, Rui
    Jing, Yuanwei
    Wang, Zhanshan
    CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 3177 - 3182
  • [46] Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case
    Raja, R.
    Anthoni, S. Marshal
    COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION, 2011, 16 (02) : 613 - 622
  • [47] Existence and global exponential stability of equilibrium for discrete-time fuzzy BAM neural networks with variable delays and impulses
    Li, Yongkun
    Wang, Chao
    FUZZY SETS AND SYSTEMS, 2013, 217 : 62 - 79
  • [48] Global exponential stability of uncertain memristor-based recurrent neural networks with mixed time delays
    Jianmin Wang
    Fengqiu Liu
    Sitian Qin
    International Journal of Machine Learning and Cybernetics, 2019, 10 : 743 - 755
  • [49] Globally exponential stability for neural networks with time-varying delays
    Shi, Lin
    Zhu, Hong
    Zhong, Shouming
    Hou, Liyuan
    APPLIED MATHEMATICS AND COMPUTATION, 2013, 219 (21) : 10487 - 10498
  • [50] Global Exponential Stability for Uncertain Dynamic Neural Networks with Discrete and Distributed Time-varying Delays
    Wu, Liang
    Ma, Baolin
    Cheng, Jianfeng
    Yin, Jingben
    2010 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-5, 2010, : 1273 - +
12345