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Simulated Annealing, High-Order Statistics and Mutual Information for Separation of Sources

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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 Simposium de la Unión Científica Internacional de Radio (XVIè : 2001 : Madrid )
dc.contributor URSI 2001
dc.contributor.author Solé-Casals, Jordi
dc.contributor.author Puntonet, Carlos G.
dc.contributor.author Rojas, I.
dc.date.accessioned 2014-03-19T11:23:44Z
dc.date.available 2014-03-19T11:23:44Z
dc.date.created 2001
dc.date.issued 2001
dc.identifier.uri http://hdl.handle.net/10854/2783
dc.description.abstract In this article, the fusion of a stochastic metaheuristic as Simulated Annealing (SA) with classical criteria for convergence of Blind Separation of Sources (BSS), is shown. Although the topic of BSS, by means of various techniques, including ICA, PCA, and neural networks, has been amply discussed in the literature, to date the possibility of using simulated annealing algorithms has not been seriously explored. From experimental results, this paper demonstrates the possible benefits offered by SA in combination with high order statistical and mutual information criteria for BSS, such as robustness against local minima and a high degree of flexibility in the energy function. en
dc.format application/pdf
dc.format.extent 2 p. ca_ES
dc.language.iso eng ca_ES
dc.rights Aquest document està subjecte a aquesta llicència Creative Commons ca_ES
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/ ca_ES
dc.subject.other Separació (Tecnologia) ca_ES
dc.title Simulated Annealing, High-Order Statistics and Mutual Information for Separation of Sources en
dc.type info:eu-repo/semantics/conferenceObject ca_ES
dc.rights.accesRights info:eu-repo/semantics/openAccess ca_ES

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