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dc.contributor.authorRamírez García, David
dc.contributor.authorSantamaría Caballero, Luis Ignacio 
dc.contributor.authorVan Vaerenbergh, Steven
dc.contributor.authorScharf, Louis L. 
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2019-03-13T16:07:27Z
dc.date.available2019-03-13T16:07:27Z
dc.date.issued2018
dc.identifier.isbn978-1-5386-9218-9
dc.identifier.otherTEC2013-41718-Res_ES
dc.identifier.otherTEC2015-69648-REDCes_ES
dc.identifier.otherTEC2015-69868-C2-1-Res_ES
dc.identifier.otherTEC2017-86921-C2-2-Res_ES
dc.identifier.otherTEC2016-75067-C4-4-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/15871
dc.description.abstractAn alternating optimization algorithm is presented and analyzed for identifying low-rank signal components, known in factor analysis terminology as common factors, that are correlated across two multiple-input multiple-output (MIMO) channels. The additive noise model at each of the MIMO channels consists of white uncorrelated noises of unequal variances plus a low-rank structured interference that is not correlated across the two channels. The low-rank components at each channel represent uncommon or channel-specific factors.es_ES
dc.description.sponsorshipThe work of D. Ram´ırez was supported by the Ministerio de Economía, Industria y Competitividad (MINECO) and AEI/FEDER funds of the E.U., under grants TEC2013- 41718-R (OTOSIS), TEC2015-69648-REDC (COMONSENS Network), TEC2015-69868-C2-1-R (ADVENTURE), and CAIMAN (TEC2017-86921-C2-2-R) and The Comunidad de Madrid under grant S2013/ICE-2845 (CASI-CAM-CM). The work of I. Santamaria and S. Van Vaerenbergh was supported by MINECO and AEI/FEDER funds of the E.U., under grant TEC2016-75067-C4-4-R (CARMEN). The work of L. Scharf was supported in part by the National Science Foundation under grant CCF-1712788.es_ES
dc.format.extent5 p.es_ES
dc.language.isoenges_ES
dc.publisherIEEEes_ES
dc.rights© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.es_ES
dc.source52nd Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 2018, 1743-1747es_ES
dc.subject.otherFactor analysises_ES
dc.subject.otherExpectation-maximizationes_ES
dc.subject.otherMaximum likelihoodes_ES
dc.subject.otherMIMO channelses_ES
dc.subject.otherMultivariate normal modeles_ES
dc.titleAn alternating optimization algorithm for two-channel factor analysis with common and uncommon factorses_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.relation.publisherVersionhttps://doi.org/10.1109/ACSSC.2018.8645457es_ES
dc.rights.accessRightsopenAccesses_ES
dc.identifier.DOI10.1109/ACSSC.2018.8645457
dc.type.versionacceptedVersiones_ES


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