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hal.structure.identifierÉcole Nationale Supérieure des Arts et Métiers [ENSAM]
dc.contributor.authorIBÁÑEZ, Rubén
hal.structure.identifierÉcole Nationale Supérieure des Arts et Métiers [ENSAM]
dc.contributor.authorABISSET, Emmanuelle
hal.structure.identifierLaboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
dc.contributor.authorAMMAR, Amine
hal.structure.identifierAragón Institute of Engineering Research [Zaragoza] [I3A]
dc.contributor.authorGONZALEZ, David
hal.structure.identifierAragón Institute of Engineering Research [Zaragoza] [I3A]
dc.contributor.authorCUETO, Elias
hal.structure.identifierLaboratori de Càlcul Numèric (LACAN) [LaCàN]
dc.contributor.authorHUERTA, Antonio
hal.structure.identifierESI Group [ESI Group]
dc.contributor.authorDUVAL, Jean Louis
hal.structure.identifierÉcole Nationale Supérieure des Arts et Métiers [ENSAM]
dc.contributor.authorCHINESTA, Francisco
dc.date.accessioned2021-05-14T09:40:59Z
dc.date.available2021-05-14T09:40:59Z
dc.date.issued2018
dc.identifier.issn1099-0526
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/76619
dc.description.abstractSparse model identification by means of data is especially cumbersome if the sought dynamics live in a high dimensional space. This usually involves the need for large amount of data, unfeasible in such a high dimensional settings. This well-known phenomenon, coined as the curse of dimensionality, is here overcome by means of the use of separate representations. We present a technique based on the same principles of the Proper Generalized Decomposition that enables the identification of complex laws in the low-data limit. We provide examples on the performance of the technique in up to ten dimensions.
dc.language.isoen
dc.titleA Multidimensional Data-Driven Sparse Identification Technique: The Sparse Proper Generalized Decomposition
dc.typeArticle de revue
dc.identifier.doi10.1155/2018/5608286
dc.subject.halSciences de l'ingénieur [physics]/Matériaux
bordeaux.journalComplexity
bordeaux.page1-11
bordeaux.volume2018
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.peerReviewedoui
hal.identifierhal-02285019
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02285019v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.title=A%20Multidimensional%20Data-Driven%20Sparse%20Identification%20Technique:%20The%20Sparse%20Proper%20Generalized%20Decomposition&rft.atitle=A%20Multidimensional%20Data-Driven%20Sparse%20Identification%20Technique:%20The%20Sparse%20Proper%20Generalized%20Decomposition&rft.jtitle=Complexity&rft.date=2018&rft.volume=2018&rft.spage=1-11&rft.epage=1-11&rft.eissn=1099-0526&rft.issn=1099-0526&rft.au=IB%C3%81%C3%91EZ,%20Rub%C3%A9n&ABISSET,%20Emmanuelle&AMMAR,%20Amine&GONZALEZ,%20David&CUETO,%20Elias&rft.genre=article


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