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Blind channel deconvolution of real world signals using source separation techniques

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dc.contributor Universitat de Vic. Escola Politècnica Superior
dc.contributor Universitat de Vic. Grup de Recerca en Tecnologies Digitals
dc.contributor International Conference on Non-Linear Speech Processing NOLISP (2005 : Barcelona)
dc.contributor.author Solé-Casals, Jordi
dc.contributor.author Monte-Moreno, Enric
dc.date.accessioned 2013-02-25T11:25:34Z
dc.date.available 2013-02-25T11:25:34Z
dc.date.created 2005
dc.date.issued 2005
dc.identifier.citation Solé Casals, J. & Monte-Moreno, E. 2005, "Blind channel deconvolution of real world signals using source separation techniques", Nonlinear Analyses and Algorithms for Speech Processing; LECTURE NOTES IN ARTIFICIAL INTELLIGENCE; International Conference on Non-Linear Speech Processing, eds. M. Faundez-Zanuy, L. Janer, A. Esposito, A. SatueVillar, J. Roure & V. EspinosaDuro, SPRINGER-VERLAG BERLIN, BERLIN; HEIDELBERGER PLATZ 3, D-14197 BERLIN, GERMANY, APR 19-22, 2005, pp. 357. ca_ES
dc.identifier.isbn 8426713653
dc.identifier.uri http://hdl.handle.net/10854/2093
dc.description.abstract In this paper we present a method for blind deconvolution of linear channels based on source separation techniques, for real word signals. This technique applied to blind deconvolution problems is based in exploiting not the spatial independence between signals but the temporal independence between samples of the signal. Our objective is to minimize the mutual information between samples of the output in order to retrieve the original signal. In order to make use of use this idea the input signal must be a non-Gaussian i.i.d. signal. Because most real world signals do not have this i.i.d. nature, we will need to preprocess the original signal before the transmission into the channel. Likewise we should assure that the transmitted signal has non-Gaussian statistics in order to achieve the correct function of the algorithm. The strategy used for this preprocessing will be presented in this paper. If the receiver has the inverse of the preprocess, the original signal can be reconstructed without the convolutive distortion. ca_ES
dc.format application/pdf
dc.format.extent 12 p. ca_ES
dc.language.iso eng ca_ES
dc.publisher Springer ca_ES
dc.rights (c) Springer, 2005
dc.rights Tots els drets reservats ca_ES
dc.subject.other Tractament del senyal ca_ES
dc.title Blind channel deconvolution of real world signals using source separation techniques ca_ES
dc.type info:eu-repo/semantics/conferenceObject ca_ES
dc.relation.publisherversion http://link.springer.com/chapter/10.1007%2F11613107_32?LI=true
dc.rights.accesRights info:eu-repo/semantics/openAccess ca_ES

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