A new sufficient condition for complete stability of cellular neural networks with delay

Author

Takahashi, Norikazu

Author_Institution

Dept. of Inf., Kyushu Univ., Fukuoka, Japan

Volume

Issue

fYear

2000

fDate

6/1/2000 12:00:00 AM

Firstpage

793

Lastpage

799

Abstract

This paper gives a new sufficient condition for cellular neural networks with delay (DCNNs) to be completely stable. A fixed-point theorem and a convergence theorem of the Gauss-Seidel method play important roles in the proof, while most conventional stability criteria were obtained by constructing Lyapunov functionals

Keywords

Lyapunov methods; cellular neural nets; convergence of numerical methods; delays; stability; stability criteria; Gauss-Seidel method; Lyapunov functionals; cellular neural networks; complete stability; convergence theorem; delay; fixed-point theorem; stability criteria; Cellular neural networks; Convergence; Delay; Equations; Gaussian processes; Image processing; Neural networks; Stability criteria; Sufficient conditions; Symmetric matrices;

fLanguage

English

Journal_Title

Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on

Publisher

ieee

ISSN

1057-7122

Type

jour

DOI

10.1109/81.852931

Filename

852931

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1360729