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dc.contributor.authorMiettinen, Jari
dc.contributor.authorNordhausen, Klaus
dc.contributor.authorOja, Hannu
dc.contributor.authorTaskinen, Sara
dc.contributor.authorVirta, Joni
dc.date.accessioned2016-09-15T05:48:46Z
dc.date.available2018-08-30T21:35:43Z
dc.date.issued2017
dc.identifier.citationMiettinen, J., Nordhausen, K., Oja, H., Taskinen, S., & Virta, J. (2017). The squared symmetric FastICA estimator. <i>Signal Processing</i>, <i>131</i>(February), 402-411. <a href="https://doi.org/10.1016/j.sigpro.2016.08.028" target="_blank">https://doi.org/10.1016/j.sigpro.2016.08.028</a>
dc.identifier.otherCONVID_26199329
dc.identifier.otherTUTKAID_71094
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/51368
dc.description.abstractIn this paper we study the theoretical properties of the deflation-based FastICA method, the original symmetric FastICA method, and a modified symmetric FastICA method, here called the squared symmetric FastICA. This modification is obtained by replacing the absolute values in the FastICA objective function by their squares. In the deflation-based case this replacement has no effect on the estimate since the maximization problem stays the same. However, in the symmetric case we obtain a different estimate which has been mentioned in the literature, but its theoretical properties have not been studied at all. In the paper we review the classic deflation-based and symmetric FastICA approaches and contrast these with the squared symmetric version of FastICA in a unified way. We find the estimating equations and derive the asymptotical properties of the squared symmetric FastICA estimator with an arbitrary choice of nonlinearity. This allows the main contribution of the paper, i.e., efficiency comparison of the estimates in a wide variety of situations using asymptotic variances of the unmixing matrix estimates.
dc.language.isoeng
dc.publisherElsevier BV; European Association for Signal Processing
dc.relation.ispartofseriesSignal Processing
dc.subject.otheraffine equivariance
dc.subject.otherlimiting normality
dc.subject.otherminimum distance index
dc.titleThe squared symmetric FastICA estimator
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201609144105
dc.contributor.laitosMatematiikan ja tilastotieteen laitosfi
dc.contributor.laitosDepartment of Mathematics and Statisticsen
dc.contributor.oppiaineTilastotiedefi
dc.contributor.oppiaineStatisticsen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2016-09-14T09:15:02Z
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange402-411
dc.relation.issn0165-1684
dc.relation.numberinseriesFebruary
dc.relation.volume131
dc.type.versionacceptedVersion
dc.rights.copyright© 2016 Elsevier B.V. This is a final draft version of an article whose final and definitive form has been published by Elsevier. Published in this repository with the kind permission of the publisher.
dc.rights.accesslevelopenAccessfi
dc.subject.ysoriippumattomien komponenttien analyysi
jyx.subject.urihttp://www.yso.fi/onto/yso/p38529
dc.relation.doi10.1016/j.sigpro.2016.08.028
dc.type.okmA1


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