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dc.contributorUniversitat de Vic. Escola Politècnica Superior
dc.contributorUniversitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributorInternational Symposium on Independent Component Analysis and Blind Signal Separation ( 4art : 2003 : Nara)
dc.contributorICA2003
dc.contributor.authorBabaie-Zadeh, Massoud
dc.contributor.authorSolé-Casals, Jordi
dc.contributor.authorJutten, Christian
dc.date.accessioned2014-03-19T11:36:28Z
dc.date.available2014-03-19T11:36:28Z
dc.date.created2003
dc.date.issued2003
dc.identifier.urihttp://hdl.handle.net/10854/2784
dc.description.abstractIn this paper, a new algorithm for blind inversion of Wiener systems is presented. The algorithm is based on minimization of mutual information of the output samples. This minimization is done through a Minimization-Projection (MP) approach, using a nonparametric “gradient” of mutual information.en
dc.formatapplication/pdf
dc.format.extent6 p.ca_ES
dc.language.isoengca_ES
dc.rightsAquest document està subjecte a aquesta llicència Creative Commonsca_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/ca_ES
dc.subject.otherTractament del senyalca_ES
dc.titleBlind Inversion of Wiener System using a minimization-projection (MP) approachen
dc.typeinfo:eu-repo/semantics/conferenceObjectca_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca_ES


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