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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | S. Udpin | en_US |
| dc.contributor.author | P. Niamsup | en_US |
| dc.date.accessioned | 2018-09-04T09:31:07Z | - |
| dc.date.available | 2018-09-04T09:31:07Z | - |
| dc.date.issued | 2013-12-01 | en_US |
| dc.identifier.issn | 1607887X | en_US |
| dc.identifier.issn | 10260226 | en_US |
| dc.identifier.other | 2-s2.0-84893654051 | en_US |
| dc.identifier.other | 10.1155/2013/325752 | en_US |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84893654051&origin=inward | en_US |
| dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/52729 | - |
| dc.description.abstract | This paper presents some global stability criteria of discrete-time neural networks with time-varying delays. Based on a discrete-type inequality, a new global stability condition for nonlinear difference equation is derived. We consider nonlinear discrete systems with time-varying delays and independence of delay time. Numerical examples are given to illustrate the effectiveness of our theoretical results. © 2013 S. Udpin and P. Niamsup. | en_US |
| dc.subject | Mathematics | en_US |
| dc.title | Global exponential stability of discrete-time neural networks with time-varying delays | en_US |
| dc.type | Journal | en_US |
| article.title.sourcetitle | Discrete Dynamics in Nature and Society | en_US |
| article.volume | 2013 | en_US |
| article.stream.affiliations | Kasetsart University | en_US |
| article.stream.affiliations | Chiang Mai University | en_US |
| article.stream.affiliations | South Carolina Commission on Higher Education | en_US |
| Appears in Collections: | CMUL: Journal Articles | |
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