Examinando por Materia "Signal processing"
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Ítem Algoritmo de estimación de parámetros y modulación de una señal recibida por un SDR(Universidad EAFIT, 2017) Toro Betancur, Verónica; Marulanda Bernal, José IgnacioÍtem Análisis de técnicas Wavelet para el desarrollo de compresores de audio(Universidad EAFIT, 2017) Medina Sánchez, Laura Victoria; Villegas Gutiérrez, Jairo AlbertoÍtem An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform(SPRINGER, 2017-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Universidad EAFIT. Departamento de Ciencias; Matemáticas y AplicacionesIn this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.Ítem An approach to emotion recognition in single-channel EEG signals using stationarywavelet transform(SPRINGER, 2017-01-01) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Villa, L.; Mejía, G.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoIn this work, we perform an approach to emotion recognition from Electroencephalography (EEG) single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology. Single channel EEG signals are decomposed by several types of wavelets and each subsignal are processed using several window sizes by performing a statistical analysis. Finally, three types of classifiers were used, obtaining accuracy rate between 50% to 87% for the emotional states such as happiness, sadness and neutrality. © Springer Nature Singapore Pte Ltd. 2017.Ítem An approach to emotion recognition in single-channel EEG signals: a mother child interaction(IOP Publishing, 2016) Gómez, A.; Quintero, L.; López, N.; Castro, J.; Gómez, A.; Quintero, L.; López, N.; Castro, J.; Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombia; Medical Technology Laboratory, Faculty of Engineering, Universidad Nacional de San Juan, Argentina; Psychology, Education and Culture Research Group Faculty of Social Science Politécnico Grancolombiano University Institution, Argentina; Universidad EAFIT. Escuela de Ciencias; agomez13@eafit.edu.co; oquinte1@eafit.edu.co; Modelado MatemáticoIn this work, we perform a first approach to emotion recognition from EEG single channel signals extracted in four (4) mother-child dyads experiment in developmental psychology -- Single channel EEG signals are analyzed and processed using several window sizes by performing a statistical analysis over features in the time and frequency domains -- Finally, a neural network obtained an average accuracy rate of 99% of classification in two emotional states such as happiness and sadnessÍtem Cerebral Cortex Atlas of Emotional States Through EEG Processing(SPRINGER, 2019-10-14) Gómez A.; Quintero O.L.; Lopez-Celani N.; Villa L.F.; Universidad EAFIT. Escuela de Ciencias; Modelado MatemáticoThis paper addresses the cerebral cortex maps construction from EEG signals getting an information simplification method for an emotional state phenomenon description. Bi-dimensional density distribution of main signal features are identified and a comparison to a previous approach is presented. Feature extraction scheme is performed via windowed EEG signals Stationary Wavelet Transform with the Daubechies Family (1–10); nine temporal and spectral descriptors are computed from the decomposed signal. Recursive feature selection method based on training a Random forest classifier using a one-vs-all scheme with the full features space, then a ranking procedure via gini importance, eliminating the bottom features and restarting the entire process over the new subset. Stopping criteria is the maximum accuracy. The main contribution is the analysis of the resulting subset features as a proxy for cerebral cortex maps looking for the cognitive processes understanding from surface signals. Identifying the common location of different emotional states in the central and frontal lobes, allowing to be strong parietal and temporal lobes differentiators for different emotions. © 2020, Springer Nature Switzerland AG.Ítem Desarrollo de un sistema basado en una interfaz cerebro computador para controlar dispositivos mecatrónicos de uso médico orientados a pacientes con discapacidad severa(Universidad EAFIT, 2013) Jiménez Franco, Luis David; Velásquez López, AlejandroEl presente trabajo muestra el proceso de diseño y desarrollo de un sistema basado en una interfaz cerebro-computador destinado a controlar una silla de ruedas eléctrica con el fin de que esta pueda ser utilizada por personas con discapacidad severa, especialmente con tetraplejía, de forma independiente -- Este trabajo hace parte de la segunda fase del proyecto “Evaluación de Interfaces Cerebro-Computador y Realidad Virtual para la Rehabilitación de Pacientes con Tetraplejía” liderado por el Grupo I+D+i en Tecnologías de la Información y las Comunicaciones en colaboración con el Grupo de Investigación en Ingeniería de Diseño (GRID) ambos pertenecientes a la Universidad EAFIT -- En la primera fase del proyecto se logró controlar un sistema Lego® Mindstorm pero sin alcanzar los resultados esperados, ya que el dispositivo no actuaba de acuerdo a la intención del usuario -- Debido a esto, se decidió en primer lugar buscar estrategias para mejorar la concordancia entre la intención del usuario y la acción ejecutada por el dispositivo, y en segundo lugar se planteó controlar ya no un Lego® Mindstorm sino una silla de ruedas eléctrica, agregarle un sistema de seguridad y realizarle una evaluación completa al sistema -- Dichos objetivos fueron alcanzados satisfactoriamente, ya que se logró controlar la silla de ruedas eléctrica mediante una interfaz cerebro-computador de forma confiable, se instaló una sensórica de seguridad y se realizó una evaluación del sistema completo que confirmó la efectividad del sistema desarrolladoÍtem Detección de puntas epilépticas en señales EEG usando wavelets y redes neuronales(Universidad EAFIT, 2013) Peña Ortega, Wilmer; Castaño G., Nelson EduardoÍtem Diseño de un analizador de motores reciprocantes de combustión interna a gasolina o a gas(Universidad EAFIT, 2010) Elejalde Sierra, Juan Sebastián; Mejía Cardona, Alejandro; Díaz Torres, Adalberto GabrielÍtem Diseño de un sistema de adquisición de datos para un motor de combustión interna de cuatro tiempos de Renault Twingo(Universidad EAFIT, 2009) Hoyos Arango, Daniel; Martínez Pinto, Leimer; Díaz Torres, Adalberto GabrielÍtem Double Fourier analysis for Emotion Identification in Voiced Speech(IOP Publishing, 2016) Sierra-Sosa, D; Bastidas, M; Ortiz P., D.; Quintero, O.L.; Sierra-Sosa, D; Bastidas, M; Ortiz P., D.; Quintero, O.L.; Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombia; Universidad EAFIT. Escuela de Ciencias; dsierras@eafit.edu.co; 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 presentedÍtem Estudio de los aspectos relevantes en el desarrollo de una iniciativa de comercio electrónico móvil en las organizaciones colombianas(Universidad EAFIT, 2010) Rodríguez Valdés, Isabel Cristina; Hernández Escobar, Julián; Paredes Ramos, Santiago AlfredoEl presente trabajo pretende mostrar los elementos más importantes relacionados con el comercio móvil: su origen, definición, evolución y estado actual, con miras a conocer el impacto (beneficios, riesgos y ventajas competitivas) que tendría la implementación de una estrategia móvil en una organización y a partir de allí generar unas recomendaciones que sirvan como guía de buenas prácticas en el momento de plantear una incursión en el mercado de los servicios móviles -- En Colombia, los consumidores están comenzando a sensibilizarse sobre el uso de los servicios móviles dada la comodidad y facilidad que estos proveen -- Sin embargo una de las grandes limitantes que se perciben al pensar en integrar la tecnología móvil en los procesos de negocio y también para realizar transacciones es la seguridad y la confiabilidad que genera al consumidor pues existe un paradigma acerca de estos aspectos relacionados con las transacciones digitales -- Así, es nuestro objetivo conocer el panorama de los servicios móviles en el mundo y en el país con el fin de recopilar la información necesaria para crear una base de conocimiento que le sea útil a las organizaciones para darse cuenta de todo lo que una estrategia dirigida al comercio móvil conlleva y como podrían mejorar su negocio si la ejecutan de la manera adecuada -- El panorama actual de la tecnología móvil e inalámbrica (servicios móviles, innovación en la tecnología, penetración de la telefonía móvil, proliferación de las redes inalámbricas, iniciativas gubernamentales y de los operadores para expandir el uso de la tecnología en la sociedad, etc.) nos muestra que se está dando un proceso de desarrollo importante, es un asunto que adquiere cada vez mayor relevancia en la sociedad y entrado a formar un rol fundamental en la vida cotidiana de las personas -- Por todo lo anterior pensamos que las empresas deben estar atentas a todos estos cambios que se presentan y aprovecharlos de la mejor manera para reinventar su forma de hacer negocios, en especial la forma de llegar a sus clientes y a sus proveedores teniendo como fin último sobresalir en un mercado que cada vez es más competitivo y dinámicoÍtem Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals(IEEE, 2014-01-01) Vasquez-Correa, J. C.; Garcia, N.; Vargas-Bonilla, J. F.; Orozco-Arroyave, J. R.; Arias-Londono, J. D.; Lucia Quintero M, O.; Vasquez-Correa, J. C.; Garcia, N.; Vargas-Bonilla, J. F.; Orozco-Arroyave, J. R.; Arias-Londono, J. D.; Lucia Quintero M, O.; Universidad EAFIT. Departamento de Ciencias; Modelado MatemáticoDetection of emotion in humans from speech signals is a recent research field. One of the scenarios where this field has been applied is in situations where the human integrity and security are at risk. In this paper we are propossing a set of features based on the Teager energy operator, and several entropy measures obtained from the decomposition signals from discrete wavelet transform to characterize different types of negative emotions such as anger, anxiety, disgust, and desperation. The features are measured in three different conditions: (1) the original speech signals, (2) the signals that are contaminated with noise, or are affected by the presence of a phone channel, and (3) the signals that are obtained after processing using an algorithm for Speech Enhancement based on Karhunen-Love Transform. According to the results, when the speech enhancement is applied, the detection of emotion in speech is increased in up to 22% compared to results obtained when the speech signal is highly contaminated with noise. © 2014 IEEE.Ítem Implementación de un sistema de simulación de carga y un sobrealimentador eléctrico en un motor de combustión interna para estudiar su desempeño(Universidad EAFIT, 2011) Solarte Henao, Stevens Mauricio; Hermández Lordui, Mónica PatriciaÍtem Manual de utilización de transductores y sistemas de adquisición de datos del laboratorio de mecánica experimental(Universidad EAFIT, 2009) Sánchez Pulgarín, Javier Hernán; Pineda Botero, Fabio AntonioÍtem Multiresolution analysis (discrete wavelet transform) through Daubechies family for emotion recognition in speech(IOP Publishing, 2016) Campo, D.; Quintero, O.L.; Bastidas, M; Campo, D.; Quintero, O.L.; Bastidas, M; Dipartimento di Ingegneria Navale, Elettrica, Elettronica e delle Telecomunicazioni (DITEN). Information and Signal Processing for Cognitive Telecommunications ISIP40, Genova, Italy; Mathematical Modeling Research Group at Mathematical Sciences Department in School of Sciences at Universidad EAFIT, Medellín, Colombia; Universidad EAFIT. Escuela de Ciencias; dcampoc@eafit.edu.co; oquinte1@eafit.edu.co; mbastida@eafit.edu.co; 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 identifyÍtem Non-intrusive detection of rotating stall in pump-turbines(ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD, 2014-10-03) Botero, F.; Hasmatuchi, V.; Roth, S.; Farhat, M.; Mecánica AplicadaWhen operated far from their optimum conditions, pump-turbines may exhibit strong hydrodynamic instabilities, often called rotating stall, which lead to substantial increase of vibration and risk of mechanical failure. In the present study, we have investigated the flow filed in a model of radial pump-turbine with the help of tuft visualization, wall pressure measurement and structure-borne noise monitoring. As the rotation speed is increased, the machine is brought from its optimum operation to runaway with zero torque on the shaft. The runaway operation is characterized by a significant increase of pressure fluctuation at the rotor-stator interaction frequency. As the speed is further increased, the flow exhibits sub-synchronous instability, which rotates at 70% of the rotation frequency. Tuft visualization clearly shows that, as the instability evolves, the flow in a given distributor channel suddenly stalls and switches to reverse pumping mode in periodic way. We have also investigated the monitoring of the rotating stall with the help of vibration signals. A specific signal processing method, based on amplitude demodulation, was developed. The use of 2 accelerometers allows for the identification of the optimum carrier frequency by computing the cyclic coherence of vibration signals. This non-intrusive method is proved to be efficient in detecting the rotating stall instability and the number of stall cells. We strongly believe that it could be implemented in full scale pump-turbines. © 2014 Elsevier Ltd.Ítem NTCCRT: A concurrent constraint framework for soft real-time music interaction(Asian Research Publishing Network, 2015-01-01) Toro, M.; Rueda, C.; Agón, C.; Assayag, G.; Toro, M.; Rueda, C.; Agón, C.; Assayag, G.; Universidad EAFIT. Departamento de Ingeniería de Sistemas; I+D+I en Tecnologías de la Información y las ComunicacionesWriting music interaction systems is not easy because their concurrent processes usually access shared resources in a non-deterministic order, often leading to unpredictable behavior. Using Pure Data (Pure Data) and Max/MSP, it is possible to program concurrency; however, it is difficult to synchronize processes based on multiple criteria. Process calculi such as the Non-deterministic Timed Concurrent Constraint (ntcc) calculus, overcome that problem by representing, declaratively, the synchronization of multiple criteria as constraints. In this article, we propose the framework Ntccrt, as a new alternative to manage concurrency in Pure Data and Max/MSP. Ntccrt is a real-time capable interpreter for ntcc. Using Ntccrt binary plugins in Pure Data, we executed models for machine improvisation and signal processing. We also analyzed two case studies: one of a machine improvisation system and one of a signal processing system. We found out that performance of both case studies is compatible with soft real-time music interaction; it means, a musician can interact with Ntccrt without noticeable delays during the interaction. © 2005 - 2015 JATIT & LLS. All rights reserved.Ítem A simple but efficient voice activity detection algorithm through Hilbert transform and dynamic threshold for speech pathologies(IOP Publishing, 2016) Ortiz P., D.; Villa, Luisa F.; Salazar, Carlos; Quintero, O.L.; Ortiz P., D.; Villa, Luisa F.; Salazar, Carlos; Quintero, O.L.; Mathematical Modeling Research Group, GRIMMAT, School of Sciences, Universidad EAFIT, Medellín, Colombia; Universidad EAFIT. Escuela de Ciencias; dpuerta1@eafit.edu.co; oquinte1@eafit.edu.co; Modelado MatemáticoA simple but efficient voice activity detector based on the Hilbert transform and a dynamic threshold is presented to be used on the pre-processing of audio signals -- The algorithm to define the dynamic threshold is a modification of a convex combination found in literature -- This scheme allows the detection of prosodic and silence segments on a speech in presence of non-ideal conditions like a spectral overlapped noise -- The present work shows preliminary results over a database built with some political speech -- The tests were performed adding artificial noise to natural noises over the audio signals, and some algorithms are compared -- Results will be extrapolated to the field of adaptive filtering on monophonic signals and the analysis of speech pathologies on futures works