Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays

Sitian Qin; Xin Shi; Guofang Chen; Jingxue Xu

doi:10.1109/ICICIP.2014.7010313

Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays

Sitian Qin
, Xin Shi
, Guofang Chen
, Jingxue Xu

Dalian University of Technology
Harbin Institute of Technology Weihai

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

1 Scopus citations

Abstract

The exponential convergence of interval Cohen-Grossberg neural network is studied in this paper. The neural network considered in this paper has the inverse-Lipschitz continuous activation and mixed delays. Based on homomorphic method and Lyapunov stability theorem, the existence, uniqueness and exponential stability of the equilibrium point of the interval Cohen-Grossberg neural network are derived. Some comparisons and numerical examples are introduced to show the improvement of the conclusions in this paper.

Original language	English
Title of host publication	5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	53-58
Number of pages	6
ISBN (Electronic)	9781479936489
DOIs	https://doi.org/10.1109/ICICIP.2014.7010313
State	Published - 14 Jan 2015
Externally published	Yes
Event	5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Dalian, Liaoning, China Duration: 18 Aug 2014 → 20 Aug 2014

Publication series

Name	5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings

Conference

Conference	5th International Conference on Intelligent Control and Information Processing, ICICIP 2014
Country/Territory	China
City	Dalian, Liaoning
Period	18/08/14 → 20/08/14

Access to Document

10.1109/ICICIP.2014.7010313

Cite this

Qin, S., Shi, X., Chen, G., & Xu, J. (2015). Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays. In 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings (pp. 53-58). Article 7010313 (5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICICIP.2014.7010313

Qin, Sitian ; Shi, Xin ; Chen, Guofang et al. / Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays. 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 53-58 (5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings).

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title = "Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays",

abstract = "The exponential convergence of interval Cohen-Grossberg neural network is studied in this paper. The neural network considered in this paper has the inverse-Lipschitz continuous activation and mixed delays. Based on homomorphic method and Lyapunov stability theorem, the existence, uniqueness and exponential stability of the equilibrium point of the interval Cohen-Grossberg neural network are derived. Some comparisons and numerical examples are introduced to show the improvement of the conclusions in this paper.",

author = "Sitian Qin and Xin Shi and Guofang Chen and Jingxue Xu",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 ; Conference date: 18-08-2014 Through 20-08-2014",

year = "2015",

month = jan,

day = "14",

doi = "10.1109/ICICIP.2014.7010313",

language = "英语",

series = "5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings",

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Qin, S, Shi, X, Chen, G & Xu, J 2015, Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays. in 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings., 7010313, 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 53-58, 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014, Dalian, Liaoning, China, 18/08/14. https://doi.org/10.1109/ICICIP.2014.7010313

Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays. / Qin, Sitian; Shi, Xin; Chen, Guofang et al.
5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2015. p. 53-58 7010313 (5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings).

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

TY - GEN

T1 - Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays

AU - Qin, Sitian

AU - Shi, Xin

AU - Chen, Guofang

AU - Xu, Jingxue

PY - 2015/1/14

Y1 - 2015/1/14

N2 - The exponential convergence of interval Cohen-Grossberg neural network is studied in this paper. The neural network considered in this paper has the inverse-Lipschitz continuous activation and mixed delays. Based on homomorphic method and Lyapunov stability theorem, the existence, uniqueness and exponential stability of the equilibrium point of the interval Cohen-Grossberg neural network are derived. Some comparisons and numerical examples are introduced to show the improvement of the conclusions in this paper.

AB - The exponential convergence of interval Cohen-Grossberg neural network is studied in this paper. The neural network considered in this paper has the inverse-Lipschitz continuous activation and mixed delays. Based on homomorphic method and Lyapunov stability theorem, the existence, uniqueness and exponential stability of the equilibrium point of the interval Cohen-Grossberg neural network are derived. Some comparisons and numerical examples are introduced to show the improvement of the conclusions in this paper.

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DO - 10.1109/ICICIP.2014.7010313

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T3 - 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings

SP - 53

EP - 58

BT - 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014

Y2 - 18 August 2014 through 20 August 2014

ER -

Qin S, Shi X, Chen G, Xu J. Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays. In 5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2015. p. 53-58. 7010313. (5th International Conference on Intelligent Control and Information Processing, ICICIP 2014 - Proceedings). doi: 10.1109/ICICIP.2014.7010313

Exponential stability of interval Cohen-Grossberg neural networks with inverse Lipschitz activation and mixed delays

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