dc.creatorFontove Herrera, Fernando
dc.date2011
dc.date.accessioned2023-07-21T15:45:37Z
dc.date.available2023-07-21T15:45:37Z
dc.identifierhttp://cimat.repositorioinstitucional.mx/jspui/handle/1008/257
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7728828
dc.descriptionThe aim of the work is to analize discrete EEG signals. For that purpose, topic models with underlying Markov chain structure are used. The models are implemented using Markov chain Monte Carlo simulation (MCMC) and several tools for the posterior analy
dc.formatapplication/pdf
dc.languageEnglish
dc.publisherCIMAT
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://creativecommons.org/about/cc0/
dc.subjectinfo:eu-repo/classification/MSC/Markov chain Monte Carlo, MCMC,Topic models, Ergodic averaging, Label switching, Gibbs sampler, Models selection, Signal analysis.
dc.subjectinfo:eu-repo/classification/cti/1
dc.subjectinfo:eu-repo/classification/cti/12
dc.subjectinfo:eu-repo/classification/cti/12
dc.titleHidden Markov Topic Models : Discrete Signal Analysis Using Markov Chain Monte Carlo
dc.typeinfo:eu-repo/semantics/masterThesis
dc.audiencestudents


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