Non-Gaussian component analysis : new ideas, new proofs, new applications

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dc.bibliographicCitation.seriesTitleWIAS Preprintseng
dc.bibliographicCitation.volume1501
dc.contributor.authorPanov, Vladimir A.
dc.date.accessioned2016-03-24T17:38:36Z
dc.date.available2019-06-28T08:05:01Z
dc.date.issued2010
dc.description.abstractIn this article, we present new ideas concerning Non-Gaussian Component Analysis (NGCA). We use the structural assumption that a high-dimensional random vector $vX$ can be represented as a sum of two componentseng
dc.description.versionpublishedVersioneng
dc.formatapplication/pdf
dc.identifier.issn0946-8633
dc.identifier.urihttps://doi.org/10.34657/2722
dc.identifier.urihttps://oa.tib.eu/renate/handle/123456789/2258
dc.language.isoengeng
dc.publisherBerlin : Weierstraß-Institut für Angewandte Analysis und Stochastikeng
dc.relation.issn0946-8633eng
dc.rights.licenseThis document may be downloaded, read, stored and printed for your own use within the limits of § 53 UrhG but it may not be distributed via the internet or passed on to external parties.eng
dc.rights.licenseDieses Dokument darf im Rahmen von § 53 UrhG zum eigenen Gebrauch kostenfrei heruntergeladen, gelesen, gespeichert und ausgedruckt, aber nicht im Internet bereitgestellt oder an Außenstehende weitergegeben werden.ger
dc.subject.ddc510eng
dc.subject.otherDimension reductioneng
dc.subject.othernon-Gaussian componentseng
dc.subject.otherNGCAeng
dc.subject.otherEDR subspaceeng
dc.subject.otherclassification problemeng
dc.subject.otherValue at Riskeng
dc.titleNon-Gaussian component analysis : new ideas, new proofs, new applicationseng
dc.typeReporteng
dc.typeTexteng
tib.accessRightsopenAccesseng
wgl.contributorWIASeng
wgl.subjectMathematikeng
wgl.typeReport / Forschungsbericht / Arbeitspapiereng
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