Delay-dependent exponential stability of neural networks with variable delays

Wu-Hua Chen; Zhi-Hong Guan; Xiaomei Lu

doi:10.1016/j.physleta.2004.04.058

Delay-dependent exponential stability of neural networks with variable delays

Wu-Hua Chen, Zhi-Hong Guan, Xiaomei Lu

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

35 Citations (Scopus)

Abstract

In this Letter, a thorough analysis of existence, uniqueness and globally exponential stability of the equilibrium point of neural networks with variable delays is presented. By applying M-matrix theory and some new analysis techniques, a new delay-dependent sufficient condition for global exponential stability is derived. The criteria obtained in this Letter extend and improve the existing ones, and a numerical example illustrate the effectiveness of our results.

Original language	English
Pages (from-to)	355-363
Number of pages	9
Journal	Physics Letters A
Volume	326
Issue number	45448
DOIs	https://doi.org/10.1016/j.physleta.2004.04.058
Publication status	Published - 2004

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10.1016/j.physleta.2004.04.058

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title = "Delay-dependent exponential stability of neural networks with variable delays",

abstract = "In this Letter, a thorough analysis of existence, uniqueness and globally exponential stability of the equilibrium point of neural networks with variable delays is presented. By applying M-matrix theory and some new analysis techniques, a new delay-dependent sufficient condition for global exponential stability is derived. The criteria obtained in this Letter extend and improve the existing ones, and a numerical example illustrate the effectiveness of our results.",

author = "Wu-Hua Chen and Zhi-Hong Guan and Xiaomei Lu",

year = "2004",

doi = "10.1016/j.physleta.2004.04.058",

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T1 - Delay-dependent exponential stability of neural networks with variable delays

AU - Chen, Wu-Hua

AU - Guan, Zhi-Hong

AU - Lu, Xiaomei

PY - 2004

Y1 - 2004

N2 - In this Letter, a thorough analysis of existence, uniqueness and globally exponential stability of the equilibrium point of neural networks with variable delays is presented. By applying M-matrix theory and some new analysis techniques, a new delay-dependent sufficient condition for global exponential stability is derived. The criteria obtained in this Letter extend and improve the existing ones, and a numerical example illustrate the effectiveness of our results.

AB - In this Letter, a thorough analysis of existence, uniqueness and globally exponential stability of the equilibrium point of neural networks with variable delays is presented. By applying M-matrix theory and some new analysis techniques, a new delay-dependent sufficient condition for global exponential stability is derived. The criteria obtained in this Letter extend and improve the existing ones, and a numerical example illustrate the effectiveness of our results.

UR - http://handle.uws.edu.au:8081/1959.7/541223

U2 - 10.1016/j.physleta.2004.04.058

DO - 10.1016/j.physleta.2004.04.058

M3 - Article

SN - 0375-9601

VL - 326

SP - 355

EP - 363

JO - Physics Letters A

JF - Physics Letters A

IS - 45448

ER -

Delay-dependent exponential stability of neural networks with variable delays

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