LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks

Sida Lin; Meiqin Liu; Yanhui Shi; Jianhai Zhang; Yaoyao Zhang; Gangfeng Yan

doi:10.1007/978-3-540-72383-7_113

LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks

Sida Lin
, Meiqin Liu
, Yanhui Shi
, Jianhai Zhang
, Yaoyao Zhang
, Gangfeng Yan

Office of Zhejiang Provincial Natural Science Foundation
Zhejiang University
Shijiazhuang Tiedao University

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

1 Scopus citations

Abstract

The global asymptotic stability of discrete-time Cohen-Grossberg neural networks (CGNNs) with or without time delays is studied in this paper. The CGNNs are transformed into discrete-time interval systems, and several sufficient conditions of asymptotic stability for these interval systems are derived by constructing some suitable Lyapunov functionals. The obtained conditions are given in the form of linear matrix inequalities that can be checked numerically and very efficiently by resorting to the MATLAB LMI Control Toolbox.

Original language	English
Title of host publication	Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
Publisher	Springer Verlag
Pages	968-976
Number of pages	9
Edition	PART 1
ISBN (Print)	9783540723820
DOIs	https://doi.org/10.1007/978-3-540-72383-7_113
State	Published - 2007
Externally published	Yes
Event	4th International Symposium on Neural Networks, ISNN 2007 - Nanjing, China Duration: 3 Jun 2007 → 7 Jun 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 1
Volume	4491 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Symposium on Neural Networks, ISNN 2007
Country/Territory	China
City	Nanjing
Period	3/06/07 → 7/06/07

Access to Document

10.1007/978-3-540-72383-7_113

Cite this

Lin, S., Liu, M., Shi, Y., Zhang, J., Zhang, Y., & Yan, G. (2007). LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings (PART 1 ed., pp. 968-976). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4491 LNCS, No. PART 1). Springer Verlag. https://doi.org/10.1007/978-3-540-72383-7_113

Lin, Sida ; Liu, Meiqin ; Shi, Yanhui et al. / LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks. Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. pp. 968-976 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1).

@inproceedings{e4d747bc7b1043d084e3e2dacd672a76,

title = "LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks",

abstract = "The global asymptotic stability of discrete-time Cohen-Grossberg neural networks (CGNNs) with or without time delays is studied in this paper. The CGNNs are transformed into discrete-time interval systems, and several sufficient conditions of asymptotic stability for these interval systems are derived by constructing some suitable Lyapunov functionals. The obtained conditions are given in the form of linear matrix inequalities that can be checked numerically and very efficiently by resorting to the MATLAB LMI Control Toolbox.",

author = "Sida Lin and Meiqin Liu and Yanhui Shi and Jianhai Zhang and Yaoyao Zhang and Gangfeng Yan",

year = "2007",

doi = "10.1007/978-3-540-72383-7\_113",

language = "英语",

isbn = "9783540723820",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

number = "PART 1",

pages = "968--976",

booktitle = "Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings",

edition = "PART 1",

note = "4th International Symposium on Neural Networks, ISNN 2007 ; Conference date: 03-06-2007 Through 07-06-2007",

}

Lin, S, Liu, M, Shi, Y, Zhang, J, Zhang, Y & Yan, G 2007, LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks. in Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 1, vol. 4491 LNCS, Springer Verlag, pp. 968-976, 4th International Symposium on Neural Networks, ISNN 2007, Nanjing, China, 3/06/07. https://doi.org/10.1007/978-3-540-72383-7_113

LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks. / Lin, Sida; Liu, Meiqin; Shi, Yanhui et al.
Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1. ed. Springer Verlag, 2007. p. 968-976 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4491 LNCS, No. PART 1).

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

TY - GEN

T1 - LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks

AU - Lin, Sida

AU - Liu, Meiqin

AU - Shi, Yanhui

AU - Zhang, Jianhai

AU - Zhang, Yaoyao

AU - Yan, Gangfeng

PY - 2007

Y1 - 2007

N2 - The global asymptotic stability of discrete-time Cohen-Grossberg neural networks (CGNNs) with or without time delays is studied in this paper. The CGNNs are transformed into discrete-time interval systems, and several sufficient conditions of asymptotic stability for these interval systems are derived by constructing some suitable Lyapunov functionals. The obtained conditions are given in the form of linear matrix inequalities that can be checked numerically and very efficiently by resorting to the MATLAB LMI Control Toolbox.

AB - The global asymptotic stability of discrete-time Cohen-Grossberg neural networks (CGNNs) with or without time delays is studied in this paper. The CGNNs are transformed into discrete-time interval systems, and several sufficient conditions of asymptotic stability for these interval systems are derived by constructing some suitable Lyapunov functionals. The obtained conditions are given in the form of linear matrix inequalities that can be checked numerically and very efficiently by resorting to the MATLAB LMI Control Toolbox.

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DO - 10.1007/978-3-540-72383-7_113

M3 - 会议稿件

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SN - 9783540723820

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings

PB - Springer Verlag

T2 - 4th International Symposium on Neural Networks, ISNN 2007

Y2 - 3 June 2007 through 7 June 2007

ER -

Lin S, Liu M, Shi Y, Zhang J, Zhang Y, Yan G. LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks. In Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings. PART 1 ed. Springer Verlag. 2007. p. 968-976. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 1). doi: 10.1007/978-3-540-72383-7_113

LMI-based approach for global asymptotic stability analysis of discrete-time Cohen-Grossberg neural networks

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