Wide-band maximum likelihood direction finding by using tree-structured EM algorithm

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buir.contributor.authorArıkan, Orhan
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888
dc.citation.epage557en_US
dc.citation.spage554en_US
dc.contributor.authorÇadallı, Nailen_US
dc.contributor.authorArıkan, Orhanen_US
dc.coverage.spatialCorfu, Greeceen_US
dc.date.accessioned2016-02-08T12:00:39Z
dc.date.available2016-02-08T12:00:39Z
dc.date.issued1996en_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.descriptionDate of Conference: 24-26 June 1996en_US
dc.descriptionConference Name: 8th Workshop on Statistical Signal and Array Processing, IEEE 1996en_US
dc.description.abstractA tree structured Expectation Maximization (EM) algorithm is proposed and applied to the wide-band angle of arrival estimation. It may be seen as a generalization on EM using the ideas of Cascade EM algorithm and Space Alternating Generalized EM algorithm. Also, for passive data acquisition, robust and efficient alternatives for the estimation of the source signals are investigated.en_US
dc.identifier.doi10.1109/SSAP.1996.534937en_US
dc.identifier.urihttp://hdl.handle.net/11693/27742
dc.language.isoEnglishen_US
dc.publisherIEEEen_US
dc.relation.isversionofhttps://doi.org/10.1109/SSAP.1996.534937en_US
dc.source.titleProceedings of the 8th Workshop on Statistical Signal and Array Processing, IEEE 1996en_US
dc.subjectData acquisitionen_US
dc.subjectOptimizationen_US
dc.subjectParameter estimationen_US
dc.subjectSensorsen_US
dc.subjectSignal processingen_US
dc.subjectTrees (mathematics)en_US
dc.subjectCascade algorithmen_US
dc.subjectDirection of arrivalsen_US
dc.subjectMeasured signalsen_US
dc.subjectSource signalsen_US
dc.subjectSpace alternating generalized algorithmen_US
dc.subjectTree structured expectation maximization algorithmen_US
dc.subjectWide band maximum Angle of arrival estimationen_US
dc.subjectAlgorithmsen_US
dc.titleWide-band maximum likelihood direction finding by using tree-structured EM algorithmen_US
dc.typeConference Paperen_US
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