000075962 001__ 75962
000075962 005__ 20200513005825.0
000075962 0247_ $$2doi$$a10.1155/2018/5608286
000075962 0248_ $$2sideral$$a109051
000075962 037__ $$aART-2018-109051
000075962 041__ $$aeng
000075962 100__ $$aIbanez, R.
000075962 245__ $$aA Multidimensional Data-Driven Sparse Identification Technique: The Sparse Proper Generalized Decomposition
000075962 260__ $$c2018
000075962 5060_ $$aAccess copy available to the general public$$fUnrestricted
000075962 5203_ $$aSparse 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.
000075962 536__ $$9info:eu-repo/grantAgreement/ES/MINECO/DPI2017-85139-C2-1-R$$9info:eu-repo/grantAgreement/ES/MINECO/DPI2015-72365-EXP$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 675919-AdMoRe$$9info:eu-repo/grantAgreement/EC/H2020/675919/EU/Empowered decision-making in simulation-based engineering: Advanced Model Reduction for real-time, inverse and optimization in industrial problems/AdMoRe$$9info:eu-repo/grantAgreement/ES/DGA/T24-17R
000075962 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000075962 590__ $$a2.591$$b2018
000075962 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b21 / 105 = 0.2$$c2018$$dQ1$$eT1
000075962 591__ $$aMULTIDISCIPLINARY SCIENCES$$b24 / 69 = 0.348$$c2018$$dQ2$$eT2
000075962 592__ $$a0.535$$b2018
000075962 593__ $$aMultidisciplinary$$c2018$$dQ1
000075962 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000075962 700__ $$aAbisset-Chavanne, E.
000075962 700__ $$aAmmar, A.
000075962 700__ $$0(orcid)0000-0003-3003-5856$$aGonzalez, D.$$uUniversidad de Zaragoza
000075962 700__ $$0(orcid)0000-0003-1017-4381$$aCueto, E.$$uUniversidad de Zaragoza
000075962 700__ $$aHuerta, A.
000075962 700__ $$aDuval, J.L.
000075962 700__ $$aChinesta, F.
000075962 7102_ $$15004$$2605$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Mec.Med.Cont. y Teor.Est.
000075962 773__ $$g18, 5608286 (2018), [11 pp]$$pComplexity$$tComplexity$$x1076-2787
000075962 8564_ $$s685137$$uhttps://zaguan.unizar.es/record/75962/files/texto_completo.pdf$$yVersión publicada
000075962 8564_ $$s100993$$uhttps://zaguan.unizar.es/record/75962/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000075962 909CO $$ooai:zaguan.unizar.es:75962$$particulos$$pdriver
000075962 951__ $$a2020-05-13-00:51:29
000075962 980__ $$aARTICLE