Global asymptotic stability and global exponential stability of continuous-time recurrent neural networks

Sanqing Hu; Jun Wang

doi:10.1109/TAC.2002.1000277

Author(s)

Sanqing Hu
Jun Wang

Detail(s)

Original language	English
Pages (from-to)	802-807
Journal / Publication	IEEE Transactions on Automatic Control
Volume	47
Issue number	5
Publication status	Published - May 2002
Externally published	Yes

Link(s)

DOI	DOI https://doi.org/10.1109/TAC.2002.1000277 Final Published version
	Check@CityULib
Link to Scopus	https://www.scopus.com/record/display.uri?eid=2-s2.0-0036576595&origin=recordpage
Permanent Link	https://scholars.cityu.edu.hk/en/publications/publication(d92ddd07-df5d-48e0-9d2f-49e5410f6f2b).html

Abstract

This note presents new results on global asymptotic stability (GAS) and global exponential stability (GES) of a general class of continuous-time recurrent neural networks with Lipschitz continuous and monotone nondecreasing activation functions. We first give three sufficient conditions for the GAS of neural networks. These testable sufficient conditions differ from and improve upon existing ones. We then extend an existing GAS result to GES one and also extend the existing GES results to more general cases with less restrictive connection weight matrices and/or partially Lipschitz activation functions.

Research Area(s)

Global asymptotic (exponential) stability, Lipschitz continuous, Recurrent neural networks

Citation Format(s)

[ RIS ] [ BibTeX ]

Global asymptotic stability and global exponential stability of continuous-time recurrent neural networks. / Hu, Sanqing; Wang, Jun.

In: IEEE Transactions on Automatic Control, Vol. 47, No. 5, 05.2002, p. 802-807.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review

Hu, S & Wang, J 2002, 'Global asymptotic stability and global exponential stability of continuous-time recurrent neural networks', IEEE Transactions on Automatic Control, vol. 47, no. 5, pp. 802-807. https://doi.org/10.1109/TAC.2002.1000277

Hu, S., & Wang, J. (2002). Global asymptotic stability and global exponential stability of continuous-time recurrent neural networks. IEEE Transactions on Automatic Control, 47(5), 802-807. https://doi.org/10.1109/TAC.2002.1000277

Hu S, Wang J. Global asymptotic stability and global exponential stability of continuous-time recurrent neural networks. IEEE Transactions on Automatic Control. 2002 May;47(5):802-807. https://doi.org/10.1109/TAC.2002.1000277

Hu, Sanqing ; Wang, Jun. / Global asymptotic stability and global exponential stability of continuous-time recurrent neural networks. In: IEEE Transactions on Automatic Control. 2002 ; Vol. 47, No. 5. pp. 802-807.