A unifying proof of global asymptotical stability of neural networks with delay

被引：8

作者：

Huang, YS ^{[1
]}

Wu, CW

机构：

[1] Pace Univ, Dept Math, Pleasantville, NY 10570 USA

[2] IBM Corp, TJ Watson Res Ctr, Yorktown Hts, NY 10598 USA

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS | 2005年 / 52卷 / 04期

关键词：

asymptotical stability; delay equations; Lyapunov functional; neural networks;

D O I：

10.1109/TCSII.2004.842023

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We present some new global stability results of neural networks with delay and show that these results generalize recently published stability results. In particular, several different stability conditions in the literature which were proved using different Lyapunov functionals; are generalized and unified by proving them using the same Lyapunov functional. We also show that under certain conditions, reversing the directions of the coupling between neurons preserves the global asymptotical stability of the neural network.

引用

页码：181 / 184

页数：4

共 50 条

[41] On the global stability of delayed neural networks
Zhang, Q
Ma, RN
Chao, W
Jin, X
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2003, 48 (05) : 794 - 797
[42] Criteria for asymptotical stability independent of delay differential equation
邱深山
刘明珠
Journal of Harbin Institute of Technology, 1999, (04) : 3 - 5
[43] A new delay-independent condition for global robust stability of neural networks with time delays
Samli, Ruya
NEURAL NETWORKS, 2015, 66 : 131 - 137
[44] Finite-time stability of the impulsive stochastic neural networks with delay
Lu C.-T.
Yu S.
Cheng P.
Kongzhi Lilun Yu Yingyong/Control Theory and Applications, 2020, 37 (01): : 187 - 192
[45] Global exponential stability of time-varying delay neural networks via razumikhin technique
Liu, B
Liu, XZ
DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2004, 11 (06): : 783 - 797
[46] Global Power Stability of Neural Networks with Impulses and Proportional Delays
Guan, Kaizhong
BULLETIN OF THE MALAYSIAN MATHEMATICAL SCIENCES SOCIETY, 2019, 42 (05) : 2237 - 2264
[47] Further improved global exponential stability result for neural networks with time-varying delay
Chen, Qiao
Liu, Xinge
Li, Xuemei
NEURAL COMPUTING & APPLICATIONS, 2022, 34 (03) : 2115 - 2132
[48] Global Power Stability of Neural Networks with Impulses and Proportional Delays
Kaizhong Guan
Bulletin of the Malaysian Mathematical Sciences Society, 2019, 42 : 2237 - 2264
[49] Further improved global exponential stability result for neural networks with time-varying delay
Qiao Chen
Xinge Liu
Xuemei Li
Neural Computing and Applications, 2022, 34 : 2115 - 2132
[50] Asymptotical stability for fractional-order Hopfield neural networks with multiple time delays
Yao, Zichen
Yang, Zhanwen
Fu, Yongqiang
Li, Jiachen
MATHEMATICAL METHODS IN THE APPLIED SCIENCES, 2022, 45 (16) : 10052 - 10069

← 1 2 3 4 5 →