Seismic Wave Separation By Means Of Robust Principal Component Analysis

dc.creatorDuarte L.T.
dc.creatorNadalin E.Z.
dc.creatorFilho K.N.
dc.creatorZanetti R.A.
dc.creatorRomano J.M.T.
dc.creatorTygel M.
dc.date2012
dc.date2015-06-25T20:25:09Z
dc.date2015-11-26T15:21:16Z
dc.date2015-06-25T20:25:09Z
dc.date2015-11-26T15:21:16Z
dc.date.accessioned2018-03-28T22:30:47Z
dc.date.available2018-03-28T22:30:47Z
dc.identifier9781467310680
dc.identifierEuropean Signal Processing Conference. , v. , n. , p. 1494 - 1498, 2012.
dc.identifier22195491
dc.identifier
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84869761549&partnerID=40&md5=7555f19eea1cbcdacc5377598be32f1f
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/90399
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/90399
dc.identifier2-s2.0-84869761549
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1260181
dc.descriptionIn this work, we investigate the application of the recently introduced signal decomposition method known as robust principal component analysis (RPCA) to the problem of wave separation in seismic data. The motivation of our research comes from the observation that the elements of the decomposition performed by RPCA can be associated with particular structures that often arise in seismic data. Results obtained considering two different situations, the separation of crossing events and the separation of diffracted waves from reflected ones, confirms that RPCA is a promising tool in seismic signal processing, outperforming the classical singular value decomposition (SVD) and the extension of the SVD based on independent component analysis in most cases. © 2012 EURASIP.
dc.description
dc.description
dc.description1494
dc.description1498
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dc.languageen
dc.publisher
dc.relationEuropean Signal Processing Conference
dc.rightsfechado
dc.sourceScopus
dc.titleSeismic Wave Separation By Means Of Robust Principal Component Analysis
dc.typeActas de congresos


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