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dc.contributor.authorLopez Valcarce, Roberto
dc.contributor.authorSala Álvarez, José
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.date.accessioned2021-04-08T10:57:53Z
dc.date.available2021-04-08T10:57:53Z
dc.date.issued2019
dc.identifier.citationLópez, R.; Sala, J. Low-rank data matrix recovery with missing values and faulty sensors. A: European Signal Processing Conference. "27th EUSIPCO 2019 European Signal Processing Conference: A Coruña, Spain: September 2-6, 2019". 2019, p. 1-5. ISBN 978-1-5386-7300-3. DOI 10.23919/EUSIPCO.2019.8903117.
dc.identifier.isbn978-1-5386-7300-3
dc.identifier.urihttp://hdl.handle.net/2117/343306
dc.description.abstractIn practice, data gathered by wireless sensor networks often belongs in a low-dimensional subspace, but it can present missing as well as corrupted values due to sensor malfunctioning and/or malicious attacks. We study the problem of Maximum Likelihood estimation of the low-rank factors of the underlying structure in such situation, and develop an Expectation-Maximization algorithm to this purpose, together with an effective initialization scheme. The proposed method outperforms previous schemes based on an initial faulty sensor identification stage, and is competitive in terms of complexity and performance with convex optimization-based matrix completion approaches.
dc.description.sponsorshipRoberto Lopez-Valcarce: Supported by Agencia Estatal de Investigacion (Spain) and the European Regional Development Fund (ERDF) under project WINTER (TEC2016-76409-C2-2-R), and by Xunta de Galicia (Agrupacion Estratéxica Consolidada de Galicia accreditation 2016-2019). Josep Sala-Alvarez: Supported by Agencia Estatal de Investigacion (Spain) and ERDF under project WINTER (TEC2016-76409-C2-1-R), and the Catalan administration (AGAUR) under 2017 SGR 578.
dc.format.extent5 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal
dc.subject.lcshWireless sensor networks
dc.subject.otherLow-rank approximation
dc.subject.otherMatrix completion
dc.subject.otherOutliers
dc.subject.otherFaulty sensors
dc.titleLow-rank data matrix recovery with missing values and faulty sensors
dc.typeConference lecture
dc.subject.lemacXarxes de sensors sense fils
dc.contributor.groupUniversitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
dc.identifier.doi10.23919/EUSIPCO.2019.8903117
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/8903117
dc.rights.accessOpen Access
local.identifier.drac30863321
dc.description.versionPostprint (author's final draft)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TEC2016-76409-C2-1-R
dc.relation.projectidinfo:eu-repo/grantAgreement/AGAUR/PRI2017-2019/2017 SGR 578
local.citation.authorLopez, R.; Sala, J.
local.citation.contributorEuropean Signal Processing Conference
local.citation.publicationName27th EUSIPCO 2019 European Signal Processing Conference: A Coruña, Spain: September 2-6, 2019
local.citation.startingPage1
local.citation.endingPage5


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