Neural network based recognition of signal patterns in application to automatic testing of rails

dc.contributor.authorCiszewski, T.
dc.contributor.authorŁukasik, Z.
dc.date.accessioned2011-02-01T11:27:11Z
dc.date.available2011-02-01T11:27:11Z
dc.date.issued2006
dc.description.abstractThe paper describes the application of neural network for recognition of signal patterns in measuring data gathered by the railroad ultrasound testing car. Digital conversion of the measuring signal allows to store and process large quantities of data. The elaboration of smart, effective and automatic procedures recognizing the obtained patterns on the basis of measured signal amplitude has been presented. The test shows only two classes of pattern recognition. In authors’ opinion if we deliver big enough quantity of training data, presented method is applicable to a system that recognizes many classes.en
dc.format.extent209758 bytescs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationAdvances in electrical and electronic engineering. 2006, vol. 5, no. 3, p. 124-127.en
dc.identifier.issn1336-1376
dc.identifier.urihttp://hdl.handle.net/10084/83782
dc.language.isoenen
dc.publisherŽilinská univerzita v Žiline. Elektrotechnická fakultaen
dc.relation.ispartofseriesAdvances in electrical and electronic engineeringen
dc.relation.urihttp://advances.utc.sk/index.php/AEEEen
dc.rightsCreative Commons Attribution 3.0 Unported (CC BY 3.0)en
dc.rights© Žilinská univerzita v Žiline. Elektrotechnická fakultaen
dc.rights.accessopenAccess
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.titleNeural network based recognition of signal patterns in application to automatic testing of railsen
dc.typearticleen
dc.type.statusPeer-reviewedcs
dc.type.versionpublishedVersioncs

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