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dc.date.accessioned2021-03-19T20:54:57Z
dc.date.available2021-03-19T20:54:57Z
dc.date.created2020-11-25T01:00:30Z
dc.date.issued2021
dc.identifier.citationStøle-Hentschel, Susanne Nieto Borge, Jose Carlos Trulsen, Karsten . The deconvolution as a method to deal with gaps in ocean wave measurements. Ocean Engineering. 2021, 219
dc.identifier.urihttp://hdl.handle.net/10852/84170
dc.description.abstractThis work introduces the deconvolution as a technique to reconstruct missing information in data. While the method was originally developed for ocean waves, it will be useful in a wider range of applications where gaps in data may alter the statistics or spikes have to be eliminated without removing extreme values. For the application to ocean waves, it is estimated that gaps as long as half of the peak period may be reconstructed well. It is possible to reconstruct data of longer gaps, however, in total the amount of missing points should be less than 50% of all points and the missing data should not be clustered.
dc.languageEN
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titleThe deconvolution as a method to deal with gaps in ocean wave measurements
dc.typeJournal article
dc.creator.authorStøle-Hentschel, Susanne
dc.creator.authorNieto Borge, Jose Carlos
dc.creator.authorTrulsen, Karsten
cristin.unitcode185,15,13,0
cristin.unitnameMatematisk institutt
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1
dc.identifier.cristin1851951
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Ocean Engineering&rft.volume=219&rft.spage=&rft.date=2021
dc.identifier.jtitleOcean Engineering
dc.identifier.volume219
dc.identifier.pagecount11
dc.identifier.doihttps://doi.org/10.1016/j.oceaneng.2020.108373
dc.identifier.urnURN:NBN:no-87002
dc.type.documentTidsskriftartikkel
dc.type.peerreviewedPeer reviewed
dc.source.issn0029-8018
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/84170/2/StoleHentschel-2021-OE-219-108373.pdf
dc.type.versionPublishedVersion
cristin.articleid108373
dc.relation.projectNFR/256466
dc.relation.projectNFR/214556


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