New delay-dependent exponential stability criteria for neural networks with variable delays

Wu-Hua Chen; Xiaomei Lu

doi:10.1016/j.physleta.2005.10.058

New delay-dependent exponential stability criteria for neural networks with variable delays

Wu-Hua Chen, Xiaomei Lu

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

17 Citations (Scopus)

Abstract

This Letter provides new exponential stability criteria for neural networks with variable delays. By applying the properties of M-matrix properties and inequality techniques, simple and improved delay-dependent exponential stability criteria are derived. These criteria extend and improve the existing ones, which is important in the design of neural networks.

Original language	English
Pages (from-to)	53-58
Number of pages	6
Journal	Physics Letters A
Volume	351
Issue number	45323
DOIs	https://doi.org/10.1016/j.physleta.2005.10.058
Publication status	Published - 2006

Access to Document

10.1016/j.physleta.2005.10.058

Cite this

@article{a4b1e909195e4fc0afdb88544842ace5,

title = "New delay-dependent exponential stability criteria for neural networks with variable delays",

abstract = "This Letter provides new exponential stability criteria for neural networks with variable delays. By applying the properties of M-matrix properties and inequality techniques, simple and improved delay-dependent exponential stability criteria are derived. These criteria extend and improve the existing ones, which is important in the design of neural networks.",

author = "Wu-Hua Chen and Xiaomei Lu",

year = "2006",

doi = "10.1016/j.physleta.2005.10.058",

language = "English",

volume = "351",

pages = "53--58",

journal = "Physics Letters A",

issn = "0375-9601",

publisher = "Elsevier North-Holland",

number = "45323",

}

TY - JOUR

T1 - New delay-dependent exponential stability criteria for neural networks with variable delays

AU - Chen, Wu-Hua

AU - Lu, Xiaomei

PY - 2006

Y1 - 2006

N2 - This Letter provides new exponential stability criteria for neural networks with variable delays. By applying the properties of M-matrix properties and inequality techniques, simple and improved delay-dependent exponential stability criteria are derived. These criteria extend and improve the existing ones, which is important in the design of neural networks.

AB - This Letter provides new exponential stability criteria for neural networks with variable delays. By applying the properties of M-matrix properties and inequality techniques, simple and improved delay-dependent exponential stability criteria are derived. These criteria extend and improve the existing ones, which is important in the design of neural networks.

UR - http://handle.uws.edu.au:8081/1959.7/541216

U2 - 10.1016/j.physleta.2005.10.058

DO - 10.1016/j.physleta.2005.10.058

M3 - Article

SN - 0375-9601

VL - 351

SP - 53

EP - 58

JO - Physics Letters A

JF - Physics Letters A

IS - 45323

ER -

New delay-dependent exponential stability criteria for neural networks with variable delays

Abstract

Access to Document

Other files and links

Fingerprint

Cite this