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An extension of the FURIA classification algorithm to low quality data through fuzzy rankings and its application to the early diagnosis of dyslexia

dc.contributor.authorPalacios Jiménez, Ana María 
dc.contributor.authorSánchez Ramos, Luciano 
dc.contributor.authorCouso Blanco, Inés 
dc.contributor.authorDestercke, S.
dc.date.accessioned2016-05-06T09:28:03Z
dc.date.available2016-05-06T09:28:03Z
dc.date.issued2016
dc.identifier.citationNeurocomputing, 176, p. 60-71 (2016); doi:10.1016/j.neucom.2014.11.088
dc.identifier.issn0925-2312
dc.identifier.urihttp://hdl.handle.net/10651/37070
dc.description.sponsorshipThis work was supported in part by the Spanish Ministry of Science and Innovation (MICINN) and the Regional Ministry of the Principality of Asturias under Grants TIN2011-24302, TIN2014- 56967-R and FC-15-GRUPIN14-073
dc.format.extentp. 60-71
dc.language.isoeng
dc.relation.ispartofNeurocomputing
dc.rights©,
dc.sourceScopus
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-84955361573&partnerID=40&md5=d04ef461997b5a6be355edfa463c1cba
dc.titleAn extension of the FURIA classification algorithm to low quality data through fuzzy rankings and its application to the early diagnosis of dyslexiaeng
dc.typejournal article
dc.identifier.doi10.1016/j.neucom.2014.11.088
dc.relation.projectIDMICINN/TIN2011-24302
dc.relation.projectIDMICINN/TIN2014-56967-R
dc.relation.projectIDMICINN/FC-15-GRUPIN14-073
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.neucom.2014.11.088


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