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

Norikazu Takahashi

doi:10.1109/81.852931

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

Norikazu Takahashi

Research output: Contribution to journal › Article › peer-review

102 Citations (Scopus)

Abstract

This paper gives a new sufficient condition for cellular neural networks with delay (DCNN's) 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.

Original language	English
Pages (from-to)	793-799
Number of pages	7
Journal	IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications
Volume	47
Issue number	6
DOIs	https://doi.org/10.1109/81.852931
Publication status	Published - Jun 2000
Externally published	Yes

Keywords

Cellular neural networks
Complete stability
Delay
Gauss-seidel method

ASJC Scopus subject areas

Electrical and Electronic Engineering

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10.1109/81.852931

Cite this

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abstract = "This paper gives a new sufficient condition for cellular neural networks with delay (DCNN's) 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 = "Cellular neural networks, Complete stability, Delay, Gauss-seidel method",

author = "Norikazu Takahashi",

note = "Funding Information: Manuscript received March 29, 1999; revised November 4, 1999. This work was supported in part by the Ministry of Education, Science, Sports, and Culture of Japan under Grant 11750330. This paper was recommended by Associate Editor B. E. Shi.",

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PY - 2000/6

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N2 - This paper gives a new sufficient condition for cellular neural networks with delay (DCNN's) 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.

AB - This paper gives a new sufficient condition for cellular neural networks with delay (DCNN's) 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.

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KW - Complete stability

KW - Delay

KW - Gauss-seidel method

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ER -

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

Abstract

Keywords

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