Escudo de la República de Colombia
Sistema Nacional de Biliotecas - Repositorio Institucional Universidad Nacional de Colombia Biblioteca Digital - Repositorio Institucional UN Sistema Nacional de Bibliotecas UN

Parametric time-frequency analysis for discrimination of non-stationary signals = [Análisis tiempo-frecuencia paramétrico para la discriminación de señales no estacionarias]

Avendaño Valencia, Luis David (2009) Parametric time-frequency analysis for discrimination of non-stationary signals = [Análisis tiempo-frecuencia paramétrico para la discriminación de señales no estacionarias]. Maestría thesis, Universidad Nacional de Colombia - Sede Manizales.

Texto completo

[img]
Vista previa
PDF - Versión Enviada
Available under License Creative Commons Attribution Non-commercial No Derivatives.

2MB

Resumen

Abstract: In this master�s thesis discrimination of non-stationary signals using time varying parametric modeling and time frequency analysis is explored. This work consists of two parts, the first, to obtain a representation for non-stationary signals by parametric modeling and parametric time-frequency representations, and the second, feature selection and extraction based on time�frequency representations and time-varying data. In this study many advantages of non-stationary signal analysis using parametric methodology will be made evident. Among them it will be found that by means of these models it is possible to determine how signal�s structure changes along time and analogously, to determine how the frequency content of a signal changes. The effectiveness of this methodology depends on three main factors, first, the choice of the model structure, which in the case of TVAR modeling would be the problem to find the order of AR model, second, estimation of the model parameters and third, selection the structure of temporal change that is imposed on the dynamics of time-variant parameters. In this aspect, a revision and evaluation of different state of the art methodologies for model structure selection, estimation of TVAR parameters and temporal structures is made. It was found that the performance of parametric methodology depends directly on these three factors; however, the main influencing factor is the structure of temporal change imposed on the estimator and how it couples with the dynamics of a time-varying signal. The second addressed problem is how to use these time varying features (matricial features) to train classifiers. Features estimated with parametric models yield a complete representation of signal�s dynamics at the cost of large dimensionality and redundancy. Thus, a review of feature extraction methods devised for time-varying and matricial data is carried out. Also, relevance analysis is generalized for the case of matricial data.

Tipo de documento:Tesis/trabajos de grado - Thesis (Maestría)
Colaborador / Asesor:Castellanos Domínguez, César Germán
Palabras clave:Procesamiento de señales; Electrónica médica; Señales fonocardiográficas; Detección de epilepsia; Signal processing; Electronics in medicine; Phonocardiographic signals; Detection of epilepsy; electroencephalografic signals
Temática:6 Tecnología (ciencias aplicadas) / Technology > 62 Ingeniería y operaciones afines / Engineering
Unidad administrativa:Sede Manizales > Facultad de Ingeniería y Arquitectura > Departamento de Ingeniería Eléctrica, Electrónica y Computación
Código ID:2087
Enviado por : Biblioteca Digital Universidad Nacional de Colombia - Sede Manizales
Enviado el día :29 Septiembre 2010 20:07
Ultima modificación:02 Mar 2011 22:01
Ultima modificación:02 Mar 2011 22:01
Exportar:Clic aquí
Estadísticas:Clic aquí
Compartir:

Solamente administradores del repositorio: página de control del ítem

Vicerrectoría de Investigación: Número uno en investigación
Indexado por:
Indexado por Scholar Google WorldCat DRIVER Registry of Open Access Repositories OpenDOAR Metabiblioteca BDCOL OAIster Red de repositorios latinoamericanos DSpace BASE Open archives La referencia Colombiae Open Access Theses and Dissertations Tesis latinoamericanas CLACSO
Este sitio web se ve mejor en Firefox