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dc.contributor.authorMeschede, M.es_ES
dc.contributor.authorStutzmann, E.es_ES
dc.contributor.authorSchimmel, Martines_ES
dc.date.accessioned2019-04-11T09:55:16Z-
dc.date.available2019-04-11T09:55:16Z-
dc.date.issued2019-02-
dc.identifier.citationGeophysical Journal International, 216(2): 1260-1275 (2019)es_ES
dc.identifier.issn0956-540X-
dc.identifier.urihttp://hdl.handle.net/10261/179889-
dc.description.abstractSecondary microseismic sources emit seismic waves over long time spans. Reoccurring signals with similar slowness and frequency therefore arrive at seismic arrays. Blind source separation techniques can be used to identify and isolate such reoccurring signals from other signals and from diffuse seismic noise. Along these lines, we use non-negative matrix factorization as blind source separation technique to decompose continuous seismic array records. We model the recorded energy as a mixture of a few components with static slowness-frequency and time-dependent amplitudes. Components and amplitudes are fitted to optimally explain the recorded seismic energy over time. These components represent secondary microseismic signals with quasi-static slowness-frequency vector and fluctuating amplitude. Each fitted component reveals the geographical origin (through the slowness-frequency vector) and time evolution of an active secondary microseism with high precision because it is separated from other signals and diffuse seismic noise. Furthermore, relative traveltimes can be automatically extracted for the signals that correspond to a specific component that can potentially be used in tomographic studies. We show two examples of seismic signals that were extracted with this technique, one focusing on P waves from the typhoons Goni and Atsani, and the other showing secondary microseism PKP signals from typhoon Glenda.es_ES
dc.description.sponsorshipThis paper was funded through the ANR (Agence National de Recherche) project number ANR-14-CE01-0012.es_ES
dc.language.isoenges_ES
dc.publisherOxford University Presses_ES
dc.relation.isversionofPublisher's versiones_ES
dc.rightsopenAccesses_ES
dc.subjectBody waveses_ES
dc.subjectSeismic noisees_ES
dc.subjectWave propagationes_ES
dc.subjectnonnegative matrix factorizationes_ES
dc.subjectAlgorithmses_ES
dc.subjectVolcanoes_ES
dc.titleBlind source separation of temporally independent microseismses_ES
dc.typeartículoes_ES
dc.identifier.doi10.1093/gji/ggy437-
dc.description.peerreviewedPeer reviewedes_ES
dc.relation.publisherversionhttps://doi.org/10.1093/gji/ggy437es_ES
dc.identifier.e-issn1365-246X-
dc.contributor.funderAgence Nationale de la Recherche (France)es_ES
dc.relation.csices_ES
oprm.item.hasRevisionno ko 0 false*
dc.identifier.funderhttp://dx.doi.org/10.13039/501100001665es_ES
dc.contributor.orcidSchimmel, Martin [0000-0003-2601-4462]es_ES
dc.type.coarhttp://purl.org/coar/resource_type/c_6501es_ES
item.openairetypeartículo-
item.cerifentitytypePublications-
item.languageiso639-1en-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
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