Novel global robust stability criteria for interval neural networks with multiple time-varying delays

被引:121
作者
Xu, SY
Lam, J
Ho, DWC
机构
[1] Univ Hong Kong, Dept Mech Engn, Hong Kong, Hong Kong, Peoples R China
[2] Nanjing Univ Sci & Technol, Dept Automat, Nanjing 210094, Peoples R China
[3] City Univ Hong Kong, Dept Math, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
global asymptotic stability; interval systems; linear matrix inequality; neural networks; time-varying delays;
D O I
10.1016/j.physleta.2005.05.016
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:322 / 330
页数:9
相关论文
共 22 条
[11]   NEURONS WITH GRADED RESPONSE HAVE COLLECTIVE COMPUTATIONAL PROPERTIES LIKE THOSE OF 2-STATE NEURONS [J].
HOPFIELD, JJ .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA-BIOLOGICAL SCIENCES, 1984, 81 (10) :3088-3092
[12]  
Kolmanovskii V., 1999, INTRO THEORY APPL FU
[13]   Global robust asymptotical stability of multi-delayed interval neural networks: an LMI approach [J].
Li, CD ;
Liao, XF ;
Zhang, RN .
PHYSICS LETTERS A, 2004, 328 (06) :452-462
[14]   Global exponential stability of a class of neural circuits [J].
Liang, XB ;
Wu, LD .
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS, 1999, 46 (06) :748-751
[15]  
Liao TL, 2000, IEEE T NEURAL NETWOR, V11, P1481, DOI 10.1109/72.883480
[16]   Delay-dependent exponential stability analysis of delayed neural networks: an LMI approach [J].
Liao, XF ;
Chen, GR ;
Sanchez, EN .
NEURAL NETWORKS, 2002, 15 (07) :855-866
[17]   Robust stability for interval Hopfield neural networks with time delay [J].
Liao, XF ;
Yu, JB .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1998, 9 (05) :1042-1045
[18]  
Liao Xiaofeng, 2003, Int J Neural Syst, V13, P171, DOI 10.1142/S012906570300142X
[19]  
Michel A. N., 2002, QUALITATIVE ANAL SYN
[20]   CELLULAR NEURAL NETWORKS WITH NONLINEAR AND DELAY-TYPE TEMPLATE ELEMENTS AND NONUNIFORM GRIDS [J].
ROSKA, T ;
CHUA, LO .
INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS, 1992, 20 (05) :469-481