Please use this identifier to cite or link to this item: https://scholarhub.balamand.edu.lb/handle/uob/639
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dc.contributor.authorChreiky, Roberten_US
dc.contributor.authorDelmaire, Gillesen_US
dc.contributor.authorPuigt, Matthieuen_US
dc.contributor.authorRoussel , Gillesen_US
dc.contributor.authorAbche, Antoineen_US
dc.date.accessioned2020-12-23T08:34:05Z-
dc.date.available2020-12-23T08:34:05Z-
dc.date.issued2017-
dc.identifier.urihttps://scholarhub.balamand.edu.lb/handle/uob/639-
dc.description.abstractSource apportionment is usually tackled with blind Positive/Non-negative Matrix factorization (PMF/NMF) methods. However, the obtained results may be poor due to the dependence between some rows of the second factor. We recently proposed to inform the estimation of this factor using some prior knowledge provided by chemists-some entries are set to some fixed values-and the sum-to-one property of each row. These constraints were recently taken into account by using a parameterization which gathers all of them. In this paper, a novel robust NMF approach able to cope with outliers is proposed. For that purpose, we consider the Huber loss function-a ℓ2-ℓ1 cost function-which is robust to outliers, contrary to the Frobenius norm classically met in NMF. We thus propose new update rules for the informed Huber NMF in the framework of the split gradient techniques. The choice of the adaptive cutoff parameter-which links both single cost functions-is discussed along this paper. The proposed approach is shown to outperform state-of-the-art methods on several source apportionment simulations involving various input SNRs and outliers.en_US
dc.format.extent6 p.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.subjectCost functionen_US
dc.subjectRobustnessen_US
dc.subjectChemicalsen_US
dc.subjectSparse matricesen_US
dc.subjectIndexesen_US
dc.subject.lcshSignal processingen_US
dc.subject.lcshInformation technologyen_US
dc.titleInformed Split Gradient Non-negative Matrix factorization using Huber cost function for source apportionmenten_US
dc.typeConference Paperen_US
dc.relation.conferenceIEEE International Symposium on Signal Processing and Information Technology (ISSPIT) (12-14 Dec. 2016 : Limassol, Cyprus)en_US
dc.contributor.affiliationDepartment of Electrical Engineeringen_US
dc.description.startpage1en_US
dc.description.endpage6en_US
dc.date.catalogued2018-05-18-
dc.description.statusPublisheden_US
dc.identifier.ezproxyURLhttp://ezsecureaccess.balamand.edu.lb/login?url=https://ieeexplore.ieee.org/document/7886011/en_US
dc.identifier.OlibID180394-
dc.relation.ispartoftextIEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2016en_US
dc.provenance.recordsourceOliben_US
crisitem.author.parentorgFaculty of Engineering-
Appears in Collections:Department of Electrical Engineering
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