Made available in DSpace on 2014-12-17T15:26:36Z (GMT). No. of bitstreams: 1 FranciscoMB.pdf: 1735858 bytes, checksum: 1307c69bd6f2b893c3fd27379c0533db (MD5) Previous issue date: 2008-09-17 / In this work we presented an exhibition of the mathematical theory of orthogonal compact support wavelets in the context of multiresoluction analysis. These are particularly attractive wavelets because they lead to a stable and very efficient algorithm, that is Fast Transform Wavelet (FWT). One of our objectives is to develop efficient algorithms for calculating the coefficients wavelet (FWT) through the pyramid algorithm of Mallat and to discuss his connection with filters Banks. We also studied the concept of multiresoluction analysis, that is the context in that wavelets can be understood and built naturally, taking an important step in the change from the Mathematical universe (Continuous Domain) for the Universe of the representation (Discret Domain) / Neste trabalho apresentamos uma exposi??o da teoria matem?tica das wavelets ortogonais de suporte compacto no contexto de an?lise de multiresolu??o. Estas wavelets s?o particularmente atraentes porque conduzem a um algoritmo est?vel e muito eficiente, isto ?, a Transformada R?pida Wavelet (FWT). Um dos nossos objetivos ? desenvolver algoritmos eficientes para o calculo dos coeficientes wavelet (FWT) atrav?s do algoritmo pir?midal de Mallat e discutir sua conex?o com Banco de Filtros. Estudamos tamb?m o conceito de an?lise de multiresolu??o, que ? o contexto em que wavelets podem ser entendidas e constru?das naturalmente, tomando um importante passo na mudan?a do universo Matem?tico (Dom?nio Cont?nuo) para o Universo da representa??o (Dom?nio Discreto).

Made available in DSpace on 2014-12-17T14:56:03Z (GMT). No. of bitstreams: 1 LuizPSM_DISSERT.pdf: 2597772 bytes, checksum: 2a89626ca2223935451ac8cbba3ad340 (MD5) Previous issue date: 2012-02-24 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / Digital signal processing (DSP) aims to extract specific information from digital signals. Digital signals are, by definition, physical quantities represented by a sequence of discrete values and from these sequences it is possible to extract and analyze the desired information. The unevenly sampled data can not be properly analyzed using standard techniques of digital signal processing. This work aimed to adapt a technique of DSP, the multiresolution analysis, to analyze unevenly smapled data, to aid the studies in the CoRoT laboratory at UFRN. The process is based on re-indexing the wavelet transform to handle unevenly sampled data properly. The was efective presenting satisfactory results / O processamento digital de sinais (PDS) tem como objetivo a extra??o de informa??es espec?ficas a partir de sinais armazenados digitalmente. Os sinais digitais s?o, por defini??o, grandezas f?sicas representadas por uma sequ?ncia de valores discretos e ? a partir dessas sequ?ncias de valores que ? poss?vel extrair e analisar as informa??es desejadas. Os sinais digitais n?o regularmente espa?ados n?o s?o corretamente analisados utilizando as t?cnicas padr?es do processamento digital de sinais. Neste trabalho teve-se o objetivo de adequar uma t?cnica de PDS, a an?lise multiresolu??o, para analisar sinais n?o regularmente espa?ados, visando auxiliar as pesquisas realizadas no laborat?rio CoRoT na UFRN. O trabalho desenvolvido consiste em uma reindexa??o da transformada Wavelet para tratar os dados n?o regularmente espa?ados de maneira adequada. O m?todo mostrou-se efetivo, apresentando resultados satisfat?rios