Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/47159

TitleGlobal exponential stability of nonautonomous neural network models with unbounded delays
Author(s)Oliveira, José J.
KeywordsCohen-Grossberg neural networks
Infinite distributed delays
Infinite discrete delays
Global exponential stability
Unbounded coefficients
Issue dateDec-2017
PublisherElsevier
JournalNeural Networks
Abstract(s)For a nonautonomous class of n-dimensional di erential system with in nite delays, we give su cient conditions for its global exponential stability, without showing the existence of an equilibrium point, or a periodic solution, or an almost periodic solution. We apply our main result to several concrete neural network models, studied in the literature, and a comparison of results is given. Contrary to usual in the literature about neural networks, the assumption of bounded coe cients is not need to obtain the global exponential stability. Finally, we present numerical examples to illustrate the e ectiveness of our results.
TypeArticle
URIhttp://hdl.handle.net/1822/47159
DOI10.1016/j.neunet.2017.09.006
ISSN0893-6080
Publisher versionhttps://www.sciencedirect.com/science/article/pii/S0893608017302083
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMAT - Artigos em revistas com arbitragem / Papers in peer review journals

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