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dc.contributor.authorZhao, Wei
dc.contributor.authorWei, Yimin
dc.contributor.authorShen, Yuehong
dc.contributor.authorGao, Yufan
dc.contributor.authorYuan, Zhigang
dc.contributor.authorXu, Pengcheng
dc.contributor.authorJian, Wei
dc.date.accessioned2015-06-29T12:35:26Z
dc.date.available2015-06-29T12:35:26Z
dc.date.issued2015-06cs
dc.identifier.citationRadioengineering. 2015 vol. 24, č. 2, s. 544-551. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/41857
dc.description.abstractThis paper deals with the optimization of kurtosis for complex-valued signals in the independent component analysis (ICA) framework, where source signals are linearly and instantaneously mixed. Inspired by the recently proposed reference-based contrast schemes, a similar contrast function is put forward, based on which a new fast fixed-point (FastICA) algorithm is proposed. The new optimization method is similar in spirit to the former classical kurtosis-based FastICA algorithm but differs in the fact that it is much more efficient than the latter in terms of computational speed, which is significantly striking with large number of samples. The performance of this new algorithm is confirmed through computer simulations.en
dc.formattextcs
dc.format.extent544-551cs
dc.format.mimetypeapplication/pdfen
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/2015/15_02_0544_0551.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectBlind source separationen
dc.subjectindependent component analysisen
dc.subjectkurtosisen
dc.subjectreference-based contrast functionsen
dc.subjectfastICAen
dc.subjectcomplex-valued signalsen
dc.titleAn Efficient Algorithm by Kurtosis Maximization in Reference-Based Frameworken
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
dc.coverage.issue2cs
dc.coverage.volume24cs
dc.identifier.doi10.13164/re.2015.0544en
dc.rights.accessopenAccessen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen


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