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Adaptive diffusion schemes for heterogeneous networks

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dc.affiliation.dptoUC3M. Departamento de Teoría de la Señal y Comunicacioneses
dc.contributor.authorFernández Bes, Jesús
dc.contributor.authorArenas García, Jerónimo
dc.contributor.authorSilva, Magno T. M.
dc.contributor.authorAzpicueta Ruiz, Luis Antonio
dc.contributor.funderComunidad de Madrides
dc.contributor.funderEuropean Commissionen
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2022-01-17T12:44:34Z
dc.date.available2022-01-17T12:44:34Z
dc.date.issued2017-11-01
dc.description.abstractIn this paper, we deal with distributed estimation problems in diffusion networks with heterogeneous nodes, i.e., nodes that either implement different adaptive rules or differ in some other aspect such as the filter structure or length, or step size. Although such heterogeneous networks have been considered from the first works on diffusion networks, obtaining practical and robust schemes to adaptively adjust the combiners in different scenarios is still an open problem. In this paper, we study a diffusion strategy specially designed and suited to heterogeneous networks. Our approach is based on two key ingredients: 1) the adaptation and combination phases are completely decoupled, so that network nodes keep purely local estimations at all times and 2) combiners are adapted to minimize estimates of the network mean-square-error. Our scheme is compared with the standard adapt-then-combine scheme and theoretically analyzed using energy conservation arguments. Several experiments involving networks with heterogeneous nodes show that the proposed decoupled adapt-then-combine approach with adaptive combiners outperforms other state-of-the-art techniques, becoming a competitive approach in these scenarios.en
dc.description.sponsorshipThe work of J. Fernandez-Bes was supported in part by Project TIN2013-41998-R and Project DPI2016-75458-R from the Spanish Ministry of Economy and Competitiveness (MINECO), Spain, in part by MULTITOOLS2HEART from CIBER-BBN through Instituto de Salud Carlos III, Spain, in part by the European Social Fund (EU) and Aragon Government through BSICoS group (T96), and in part by the European Research Council (ERC) through Project ERC-2014-StG 638284. The work of J. Arenas-García was supported in part by MINECO Project TEC2014-52289-R and in part by Comunidad de Madrid Project PRICAM S2013/ICE2933. The work of M. T. M. Silva was supported in part by CNPq under Grant 304275/2014-0, and in part by FAPESP under Grant 2012/24835-1. The work of L. A. Azpicueta-Ruiz was supported in part by Comunidad de Madrid under Grant CASI-CAM-CM (id. S2013/ICE-2845), in part by the Spanish Ministry of Economy and Competitiveness under Grants DAMA TIN2015-70308-REDT and TEC2014-52289-R, and in part by the European Union.en
dc.format.extent14
dc.identifier.bibliographicCitationFernandez-Bes, J., Arenas-Garcia, J., Silva, M. T. M. & Azpicueta-Ruiz, L. A. (2017). Adaptive Diffusion Schemes for Heterogeneous Networks. IEEE Transactions on Signal Processing, 65(21), 5661–5674.en
dc.identifier.doihttps://doi.org/10.1109/TSP.2017.2740199
dc.identifier.issn1053-587X
dc.identifier.publicationfirstpage5661
dc.identifier.publicationissue21
dc.identifier.publicationlastpage5674
dc.identifier.publicationtitleIEEE Transactions on Signal Processingen
dc.identifier.publicationvolume65
dc.identifier.urihttps://hdl.handle.net/10016/33889
dc.identifier.uxxiAR/0000020471
dc.language.isoengen
dc.publisherIEEEen
dc.relation.projectIDComunidad de Madrid. S2013/ICE-2845es
dc.relation.projectIDGobierno de España. TEC2014-52289-Res
dc.relation.projectIDGobierno de España. TIN2015-70308-REDTes
dc.relation.projectIDGobierno de España. TIN2013-41998-Res
dc.relation.projectIDGobierno de España. DPI2016-75458-Res
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/638284
dc.relation.projectIDComunidad de Madrid. S2013/ICE2933es
dc.rights© 2017, IEEE.en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaElectrónicaes
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherAdaptive networksen
dc.subject.otherDiffusion networksen
dc.subject.otherDistributed estimationen
dc.subject.otherLeast-squaresen
dc.subject.otherMean-square performanceen
dc.titleAdaptive diffusion schemes for heterogeneous networksen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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