Examinando por Autor "Bastidas, M."
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Ítem Double Fourier analysis for Emotion Identification in Voiced Speech(IOP PUBLISHING LTD, 2016-01-01) Sierra-Sosa, D.; Bastidas, M.; Ortiz, P.D.; Quintero, O.L.; Sierra-Sosa, D.; Bastidas, M.; Ortiz, P.D.; Quintero, O.L.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoWe propose a novel analysis alternative, based on two Fourier Transforms for emotion recognition from speech. Fourier analysis allows for display and synthesizes different signals, in terms of power spectral density distributions. A spectrogram of the voice signal is obtained performing a short time Fourier Transform with Gaussian windows, this spectrogram portraits frequency related features, such as vocal tract resonances and quasi-periodic excitations during voiced sounds. Emotions induce such characteristics in speech, which become apparent in spectrogram time-frequency distributions. Later, the signal time-frequency representation from spectrogram is considered an image, and processed through a 2-dimensional Fourier Transform in order to perform the spatial Fourier analysis from it. Finally features related with emotions in voiced speech are extracted and presented.Ítem Estudio de la presencia y la relación entre la aparición de criaderos de Aedes Aegypti y la aparición de casos en el municipio de Bello, Antioquia(Universidad EAFIT, 2013) Bastidas, M.; Quintero, O. L.; Universidad EAFIT. Escuela de Ciencias. Grupo de Investigación Modelado MatemáticoÍtem Information retrieval on documents methodology based on entropy filtering methodologies(Inderscience Enterprises Ltd., 2015-01-01) Montoya, O.L.Q.; Villa, L.F.; Muñoz, S.; Arenas, A.C.R.; Bastidas, M.; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoInformation retrieval problem occurs when the target information is not available 'literally' into the set of documents. In problems in which the goal is to find 'hidden' information, it is important to develop hybrid methodologies or improve and design a new one. In this work the authors are dealing with identifying the most informative piece of data on a collection of documents, in order to obtain the best result on a posterior fuzzy clustering stage. The aim is to find similarities between the documents and a reference target, to establish relationships related to a non-literal feature. We propose to apply the well-known entropy term weighting scheme and then show a posterior different procedures to the right election of the interest data. This procedure brings the biggest amount of information within the smallest amount of data. Applying a specific selection procedure for a group of words, gives more information to differentiate and separate the documents after using the entropy weighting. This returns considerable results on the processing time and the right fuzzy clustering of the documents collection. Copyright © 2015 Inderscience Enterprises Ltd.Ítem Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech.(IOP PUBLISHING LTD, 2016-01-01) Campo, D.; Quintero, O.L.; Bastidas, M.; Campo, D.; Quintero, O.L.; Bastidas, M.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoWe propose a study of the mathematical properties of voice as an audio signal. This work includes signals in which the channel conditions are not ideal for emotion recognition. Multiresolution analysis- discrete wavelet transform - was performed through the use of Daubechies Wavelet Family (Db1-Haar, Db6, Db8, Db10) allowing the decomposition of the initial audio signal into sets of coefficients on which a set of features was extracted and analyzed statistically in order to differentiate emotional states. ANNs proved to be a system that allows an appropriate classification of such states. This study shows that the extracted features using wavelet decomposition are enough to analyze and extract emotional content in audio signals presenting a high accuracy rate in classification of emotional states without the need to use other kinds of classical frequency-time features. Accordingly, this paper seeks to characterize mathematically the six basic emotions in humans: boredom, disgust, happiness, anxiety, anger and sadness, also included the neutrality, for a total of seven states to identify.Ítem Solución Numérica de Ecuaciones Diferenciales Parciales(Universidad EAFIT, 2013) Bastidas, M.; Marin, Freddy; Universidad EAFIT. Escuela de Ciencias. Grupo de Investigación Modelado Matemático