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Title Sonification and augmented data sets in binary classification
Author El-Azm, Fares
Supervisor Hansen, Lars Kai (Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark)
Institution Technical University of Denmark, DTU, DK-2800 Kgs. Lyngby, Denmark
Thesis level Master's thesis
Year 2005
Abstract In the thesis an auditory browser based on granular synthesis is designed and implemented to aid in browsing through long EEG time courses. This application can be used when ICA is applied to EEG signals as a means of decontamination and is intended to accelerate the identification of artifactual time courses, though this was not confirmed through testing. Furthermore, an introduction to the rather young field of sonification and EEG sonification is presented, also including introductory chapters on auditory perception and sound synthesis. Concepts in classification are introduced and the idea of augmented data sets using PCA and ICA is investigated. It is shown that augmenting data sets can "supervise" PCA and ICA, though this was seen to be especially true for PCA.
Imprint Department of Informatics and Mathematical Modeling, Technical University of Denmark, DTU : DK-2800 Kgs. Lyngby, Denmark
Pages 129
Keywords Sonification; classification; EEG; granular synthesis; auditory perception; sound synthesis; augmented data sets; ICA; PCA
Fulltext
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Admin Creation date: 2006-06-22    Update date: 2012-12-19    Source: dtu    ID: 185825    Original MXD