Stability analysis for Cohen-Grossberg neural networks with time-varying delays

Wu-Hua Chen; Wei Xing Zheng

Stability analysis for Cohen-Grossberg neural networks with time-varying delays

Wu-Hua Chen
, Wei Xing Zheng

School of Computer, Data & Mathematical Sciences

Research output: Chapter in Book / Conference Paper › Conference Paper

Abstract

The problems of existence, uniqueness and global exponential stability of the equilibrium of Cohen-Grossberg neural networks with time-varying delays are investigated in this paper. A new approach is developed to establish delay-independent/dependent sufficient conditions for global exponential stability. The results obtained can be easily checked in practice and do not require the delays to be constant or differentiate. In particular, our delay-dependent exponential stability conditions give explicitly the allowable upper bound of the delays that guarantees stability of Cohen-Grossberg neural networks, and are applicable to the case when the non-delayed terms cannot dominate the delayed terms. The effectiveness of the new results are further illustrated by numerical examples in comparison with the existing results.

Original language	English
Title of host publication	2006 IEEE International Symposium on Circuits and Systems. ISCAS 2006. Proceedings
Publisher	IEEE
Number of pages	4
ISBN (Print)	0780393902
Publication status	Published - 2006
Event	IEEE International Symposium on Circuits and Systems - Duration: 20 May 2012 → …

Conference

Conference	IEEE International Symposium on Circuits and Systems
Period	20/05/12 → …

Keywords

time delay systems
neural nets
Cohen-Grossberg neural networks
stability
asymptotic stability

Cite this

@inproceedings{1c95e01b2b3f4f81b4f50ae59f38837b,

title = "Stability analysis for Cohen-Grossberg neural networks with time-varying delays",

abstract = "The problems of existence, uniqueness and global exponential stability of the equilibrium of Cohen-Grossberg neural networks with time-varying delays are investigated in this paper. A new approach is developed to establish delay-independent/dependent sufficient conditions for global exponential stability. The results obtained can be easily checked in practice and do not require the delays to be constant or differentiate. In particular, our delay-dependent exponential stability conditions give explicitly the allowable upper bound of the delays that guarantees stability of Cohen-Grossberg neural networks, and are applicable to the case when the non-delayed terms cannot dominate the delayed terms. The effectiveness of the new results are further illustrated by numerical examples in comparison with the existing results.",

keywords = "time delay systems, neural nets, Cohen-Grossberg neural networks, stability, asymptotic stability",

author = "Wu-Hua Chen and Zheng, \{Wei Xing\}",

year = "2006",

language = "English",

isbn = "0780393902",

booktitle = "2006 IEEE International Symposium on Circuits and Systems. ISCAS 2006. Proceedings",

publisher = "IEEE",

note = "IEEE International Symposium on Circuits and Systems ; Conference date: 20-05-2012",

}

TY - GEN

T1 - Stability analysis for Cohen-Grossberg neural networks with time-varying delays

AU - Chen, Wu-Hua

AU - Zheng, Wei Xing

PY - 2006

Y1 - 2006

N2 - The problems of existence, uniqueness and global exponential stability of the equilibrium of Cohen-Grossberg neural networks with time-varying delays are investigated in this paper. A new approach is developed to establish delay-independent/dependent sufficient conditions for global exponential stability. The results obtained can be easily checked in practice and do not require the delays to be constant or differentiate. In particular, our delay-dependent exponential stability conditions give explicitly the allowable upper bound of the delays that guarantees stability of Cohen-Grossberg neural networks, and are applicable to the case when the non-delayed terms cannot dominate the delayed terms. The effectiveness of the new results are further illustrated by numerical examples in comparison with the existing results.

AB - The problems of existence, uniqueness and global exponential stability of the equilibrium of Cohen-Grossberg neural networks with time-varying delays are investigated in this paper. A new approach is developed to establish delay-independent/dependent sufficient conditions for global exponential stability. The results obtained can be easily checked in practice and do not require the delays to be constant or differentiate. In particular, our delay-dependent exponential stability conditions give explicitly the allowable upper bound of the delays that guarantees stability of Cohen-Grossberg neural networks, and are applicable to the case when the non-delayed terms cannot dominate the delayed terms. The effectiveness of the new results are further illustrated by numerical examples in comparison with the existing results.

KW - time delay systems

KW - neural nets

KW - Cohen-Grossberg neural networks

KW - stability

KW - asymptotic stability

UR - http://handle.uws.edu.au:8081/1959.7/36205

M3 - Conference Paper

SN - 0780393902

BT - 2006 IEEE International Symposium on Circuits and Systems. ISCAS 2006. Proceedings

PB - IEEE

T2 - IEEE International Symposium on Circuits and Systems

Y2 - 20 May 2012

ER -

Stability analysis for Cohen-Grossberg neural networks with time-varying delays

Abstract

Conference

Keywords

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