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Please use this identifier to cite or link to this item: https://ptsldigital.ukm.my/jspui/handle/123456789/578107
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dc.contributor.authorAbu Hassan Shaari Mohd. Nor (Universiti Kebangsaan Malaysia)
dc.date.accessioned2023-11-06T02:58:30Z-
dc.date.available2023-11-06T02:58:30Z-
dc.date.issued2009-07
dc.identifier.issn0128-7680
dc.identifier.otherukmvital:131125
dc.identifier.urihttps://ptsldigital.ukm.my/jspui/handle/123456789/578107-
dc.descriptionExpectation Maximization (EM) algorithm has experienced a significant increase in terms of usage in many fields of study. In this paper, the performance of the said algorithm in finding the Maximum Likelihood for the Gaussian Mixed Models (GMM), a probabilistic model normally used in fraud detection and recognizing a person’s voice in speech recognition field, is shown and discussed. At the end of the paper, some suggestions for future research works will also be given.
dc.language.isoen
dc.publisherUniversiti Putra Malaysia Press
dc.relation.haspartPertanika Journal of Tropical Agricultural Science
dc.relation.urihttp://www.pertanika.upm.edu.my/view_archives.php?journal=JST-17-2-7
dc.rightsUniversiti Putra Malaysia Press
dc.subjectExpectation Maximization (EM)
dc.subjectGaussian Mixed Models (GMM)
dc.subjectBox and Muller Transformation
dc.titleThe performance of expectation maximization (EM) algorithm in gaussian mixed models (GMM)
dc.typeJournal Article
dc.format.volume17
dc.format.pages231-243
dc.format.issue2
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