Robust stability analysis of delayed neural networks with polytopic type uncertainties

Yong He; Qing Guo Wang; Wei Xing Zheng

doi:10.1109/TENCON.2005.301253

Robust stability analysis of delayed neural networks with polytopic type uncertainties

Yong He, Qing Guo Wang, Wei Xing Zheng

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We investigate the problem of global robust stability for delayed neural networks in this paper. We first utilize the free-weighting matrices to express the relationship between the terms in the system equation, and then apply the S-procedure to derive a stability condition for delayed neural networks. Next, we extend this result so as to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. Finally, we demonstrate the usefulness of the obtained global robust stability criterion and its improvement over the existing results by using a numerical example given in [21] for interval delayed neural networks.

Original language	English
Title of host publication	TENCON 2005 - 2005 IEEE Region 10 Conference
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	0780393112, 9780780393110
DOIs	https://doi.org/10.1109/TENCON.2005.301253
Publication status	Published - 2005
Externally published	Yes
Event	TENCON 2005 - 2005 IEEE Region 10 Conference - Melbourne, Australia Duration: 21 Nov 2005 → 24 Nov 2005

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume	2007
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Conference

Conference	TENCON 2005 - 2005 IEEE Region 10 Conference
Country/Territory	Australia
City	Melbourne
Period	21/11/05 → 24/11/05

Keywords

Delayed neural networks
Global robust stability
Linear matrix inequality (LMI)
Parameter-dependent Lyapunov functional
Polytopic type uncertainties

ASJC Scopus subject areas

Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/TENCON.2005.301253

Cite this

He, Y., Wang, Q. G., & Zheng, W. X. (2005). Robust stability analysis of delayed neural networks with polytopic type uncertainties. In TENCON 2005 - 2005 IEEE Region 10 Conference Article 4085363 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2007). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.2005.301253

@inproceedings{1df38e811e0645c59ce4bd72136bbe27,

title = "Robust stability analysis of delayed neural networks with polytopic type uncertainties",

abstract = "We investigate the problem of global robust stability for delayed neural networks in this paper. We first utilize the free-weighting matrices to express the relationship between the terms in the system equation, and then apply the S-procedure to derive a stability condition for delayed neural networks. Next, we extend this result so as to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. Finally, we demonstrate the usefulness of the obtained global robust stability criterion and its improvement over the existing results by using a numerical example given in [21] for interval delayed neural networks.",

keywords = "Delayed neural networks, Global robust stability, Linear matrix inequality (LMI), Parameter-dependent Lyapunov functional, Polytopic type uncertainties",

author = "Yong He and Wang, {Qing Guo} and Zheng, {Wei Xing}",

year = "2005",

doi = "10.1109/TENCON.2005.301253",

language = "English",

isbn = "0780393112",

series = "IEEE Region 10 Annual International Conference, Proceedings/TENCON",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "TENCON 2005 - 2005 IEEE Region 10 Conference",

address = "United States",

note = "TENCON 2005 - 2005 IEEE Region 10 Conference ; Conference date: 21-11-2005 Through 24-11-2005",

}

He, Y, Wang, QG & Zheng, WX 2005, Robust stability analysis of delayed neural networks with polytopic type uncertainties. in TENCON 2005 - 2005 IEEE Region 10 Conference., 4085363, IEEE Region 10 Annual International Conference, Proceedings/TENCON, vol. 2007, Institute of Electrical and Electronics Engineers Inc., TENCON 2005 - 2005 IEEE Region 10 Conference, Melbourne, Australia, 21/11/05. https://doi.org/10.1109/TENCON.2005.301253

Robust stability analysis of delayed neural networks with polytopic type uncertainties. / He, Yong; Wang, Qing Guo; Zheng, Wei Xing.
TENCON 2005 - 2005 IEEE Region 10 Conference. Institute of Electrical and Electronics Engineers Inc., 2005. 4085363 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2007).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Robust stability analysis of delayed neural networks with polytopic type uncertainties

AU - He, Yong

AU - Wang, Qing Guo

AU - Zheng, Wei Xing

PY - 2005

Y1 - 2005

N2 - We investigate the problem of global robust stability for delayed neural networks in this paper. We first utilize the free-weighting matrices to express the relationship between the terms in the system equation, and then apply the S-procedure to derive a stability condition for delayed neural networks. Next, we extend this result so as to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. Finally, we demonstrate the usefulness of the obtained global robust stability criterion and its improvement over the existing results by using a numerical example given in [21] for interval delayed neural networks.

AB - We investigate the problem of global robust stability for delayed neural networks in this paper. We first utilize the free-weighting matrices to express the relationship between the terms in the system equation, and then apply the S-procedure to derive a stability condition for delayed neural networks. Next, we extend this result so as to establish a global robust stability criterion for delayed neural networks with polytopic type uncertainties. Finally, we demonstrate the usefulness of the obtained global robust stability criterion and its improvement over the existing results by using a numerical example given in [21] for interval delayed neural networks.

KW - Delayed neural networks

KW - Global robust stability

KW - Linear matrix inequality (LMI)

KW - Parameter-dependent Lyapunov functional

KW - Polytopic type uncertainties

UR - http://www.scopus.com/inward/record.url?scp=34249319833&partnerID=8YFLogxK

U2 - 10.1109/TENCON.2005.301253

DO - 10.1109/TENCON.2005.301253

M3 - Conference contribution

AN - SCOPUS:34249319833

SN - 0780393112

SN - 9780780393110

T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON

BT - TENCON 2005 - 2005 IEEE Region 10 Conference

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - TENCON 2005 - 2005 IEEE Region 10 Conference

Y2 - 21 November 2005 through 24 November 2005

ER -

Robust stability analysis of delayed neural networks with polytopic type uncertainties

Abstract

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Keywords

ASJC Scopus subject areas

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