Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/13163

TitleGlobal stability of a Cohen-Grossberg neural network with both time-varying and continuous distributed delays
Author(s)Oliveira, José J.
KeywordsCohen-Grossberg neural network
Unbounded delay
Time-varying delay
Distributed delay
Global asymptotic stability
Global exponential stability
Issue dateOct-2011
PublisherElsevier
JournalNonlinear Analysis: Real World Applications
Abstract(s)In this paper, a generalized neural network of Cohen-Grossberg type with both discrete time-varying and distributed unbounded delays is considered. Based on M-matrix theory, sufficient conditions are established to ensure the existence and global attractivity of an equilibrium point. The global exponential stability of the equilibrium is also addressed, but for the model with bounded discrete time-varying delays. A comparison of results shows that these results generalize and improve some earlier publications.
TypeArticle
URIhttp://hdl.handle.net/1822/13163
DOI10.1016/j.nonrwa.2011.04.012
ISSN1468-1218
Publisher versionhttp://www.sciencedirect.com/
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals
DMA - Artigos (Papers)

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