@MASTERSTHESIS\{IMM2005-03975,
    author       = "F. El-Azm",
    title        = "Sonification and augmented data sets in binary classification",
    year         = "2005",
    keywords     = "Sonification, classification, {EEG,} granular synthesis, auditory perception, sound synthesis, augmented data sets, {ICA,} {PCA}",
    school       = "Informatics and Mathematical Modelling, Technical University of Denmark, {DTU}",
    address      = "Richard Petersens Plads, Building 321, {DK-}2800 Kgs. Lyngby",
    type         = "",
    note         = "Supervised by Prof. Lars Kai Hansen",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/3975-full.html",
    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}."
}