Wavelets e polinômios com coeficientes de Fibonacci
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Data
2016-12-19
Autores
Gossler, Fabrício Ely [UNESP]
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Universidade Estadual Paulista (Unesp)
Resumo
Existem diferentes tipos de funções wavelets que podem ser utilizadas na Transformada Wavelet. Na maioria das vezes, a função wavelet escolhida para a análise de um determinado sinal vai ser aquela que melhor se ajusta no domínio tempo-frequência do mesmo. Existem vários tipos de funções wavelets que podem ser escolhidas para certas aplicações, sendo que algumas destas pertencem a conjuntos específicos denominados de famílias wavelets, tais como a Haar, Daubechies, Symlets, Morlet, Meyer e Gaussianas. Nesse trabalho é apresentada uma nova família de funções wavelets geradas a partir de polinômios com coeficientes de Fibonacci (FCPs). Essa família recebe o nome de Golden, e cada membro desta é obtido por uma derivada de ordem n do quociente entre dois FCPs distintos. As Golden wavelets foram deduzidas através das observações de que, em alguns casos, a derivada de ordem n, do quociente entre dois FCPs distintos, resulta em uma função que possui as características de uma onda de duração curta. Como aplicação, algumas wavelets apresentadas no decorrer deste trabalho são utilizadas na classificação de arritmias cardíacas em sinais de eletrocardiograma, que foram extraídos da base de dados do MIT-BIH arrhythmia database.
There exist different types of wavelet functions that can be used in the Wavelet Transform. In most cases, the wavelet function chosen for the analysis of a given signal will be the one that best adjusts in the time-frequency domain of the same signal. There are many types of wavelet functions that can be chosen for certain applications, some of which belong to specific sets called wavelet families, such as Haar, Daubechies, Symlets, Morlet, Meyer, and Gaussians. In this work a new wavelet functions family generated from Fibonacci-coefficients polynomials (FCPs) is presented. This family is called Golden, and each member is obtained by the n-th derivative of the quotient between two distinct FCPs. The Golden wavelets were deduced from the observations that in some cases the n-th derivative of the quotient between two distinct FCPs results in a function that has the characteristics of a short-duration wave. As an application, some wavelets presented in the course of this work are used to cardiac arrhythmia classification in electrocardiogram signals, which were extracted from the MITBIH arrhythmia database.
There exist different types of wavelet functions that can be used in the Wavelet Transform. In most cases, the wavelet function chosen for the analysis of a given signal will be the one that best adjusts in the time-frequency domain of the same signal. There are many types of wavelet functions that can be chosen for certain applications, some of which belong to specific sets called wavelet families, such as Haar, Daubechies, Symlets, Morlet, Meyer, and Gaussians. In this work a new wavelet functions family generated from Fibonacci-coefficients polynomials (FCPs) is presented. This family is called Golden, and each member is obtained by the n-th derivative of the quotient between two distinct FCPs. The Golden wavelets were deduced from the observations that in some cases the n-th derivative of the quotient between two distinct FCPs results in a function that has the characteristics of a short-duration wave. As an application, some wavelets presented in the course of this work are used to cardiac arrhythmia classification in electrocardiogram signals, which were extracted from the MITBIH arrhythmia database.
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Palavras-chave
Polinômios com coeficientes de Fibonacci, Wavelets, Classificação de arritmias cardíacas, Fibonacci-coefficient polynomials, Cardiac arrhythmia classification