A New Method for Complete Stability Analysis of Cellular Neural Networks With Time Delay

Author

Chen, Wu-Hua ; Zheng, Wei Xing

Author_Institution

Sch. of Comput. & Math., Univ. of Western Sydney, Sydney, NSW, Australia

Volume

21

Issue

7

fYear

2010

fDate

7/1/2010 12:00:00 AM

Firstpage

1126

Lastpage

1139

Abstract

This paper presents new complete stability results for delayed cellular neural networks (DCNNs). A novel method is proposed for complete stability analysis of DCNNs. By applying the M-matrix theory and introducing some new estimation techniques on the solutions of DCNNs, a simple and improved complete stability criterion is derived. The new criterion unifies the delay-dependent and delay-independent complete stability conditions for DCNNs. Moreover, the obtained delay-dependent criterion can give a larger upper bound of the time delay than the existing ones such that the complete stability can still be retained. Numerical examples are presented which show that the new complete stability results for DCNNs are compared favorably with the existing results.

Keywords

asymptotic stability; cellular neural nets; delays; matrix algebra; M-matrix theory; cellular neural networks; delay dependent; delay independent; estimation techniques; stability analysis; time delay; Cellular neural networks (CNNs); M-matrix; complete stability; delay-independent/delay-dependent criterion; time-delay; Algorithms; Animals; Computer Simulation; Neural Networks (Computer); Time Factors;

fLanguage

English

Journal_Title

Neural Networks, IEEE Transactions on

Publisher

ieee

Conference_Location

6/14/2010 12:00:00 AM

ISSN

1045-9227

Type

jour

DOI

10.1109/TNN.2010.2048925

Filename

5484597