931 resultados para Transformada wavelet discreta


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Un dels principals problemes quan es realitza un anàlisi de contorns és la gran quantitat de dades implicades en la descripció de la figura. Per resoldre aquesta problemàtica, s’aplica la parametrització que consisteix en obtenir d’un contorn unes dades representatives amb els mínims coeficients possibles, a partir dels quals es podrà reconstruir de nou sense pèrdues molt evidents d’informació. En figures de contorns tancats, la parametrització més estudiada és l’aplicació de la transformada discreta de Fourier (DFT). Aquesta s’aplica a la seqüència de valors que descriu el comportament de les coordenades x i y al llarg de tots els punts que formen el traç. A diferència, en els contorns oberts no es pot aplicar directament la DFT ja que per fer-ho es necessita que el valor de x i de y siguin iguals tan en el primer punt del contorn com en l’últim. Això és degut al fet que la DFT representa sense error senyals periòdics. Si els senyals no acaben en el mateix punt, representa que hi ha una discontinuïtat i apareixen oscil·lacions a la reconstrucció. L’objectiu d’aquest treball és parametritzar contorns oberts amb la mateixa eficiència que s’obté en la parametrització de contorns tancats. Per dur-ho a terme, s’ha dissenyat un programa que permet aplicar la DFT en contorns oberts mitjançant la modificació de les seqüencies de x i y. A més a més, també utilitzant el programari Matlab s’han desenvolupat altres aplicacions que han permès veure diferents aspectes sobre la parametrització i com es comporten els Descriptors El·líptics de Fourier (EFD). Els resultats obtinguts han demostrat que l’aplicació dissenyada permet la parametrització de contorns oberts amb compressions òptimes, fet que facilitarà l’anàlisi quantitatiu de formes en camps com l’ecologia, medicina, geografia, entre d’altres.

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Signal processing methods based on the combined use of the continuous wavelet transform (CWT) and zero-crossing technique were applied to the simultaneous spectrophotometric determination of perindopril (PER) and indapamide (IND) in tablets. These signal processing methods do not require any priory separation step. Initially, various wavelet families were tested to identify the optimum signal processing giving the best recovery results. From this procedure, the Haar and Biorthogonal1.5 continuous wavelet transform (HAAR-CWT and BIOR1.5-CWT, respectively) were found suitable for the analysis of the related compounds. After transformation of the absorbance vectors by using HAAR-CWT and BIOR1.5-CWT, the CWT-coefficients were drawn as a graph versus wavelength and then the HAAR-CWT and BIOR1.5-CWT spectra were obtained. Calibration graphs for PER and IND were obtained by measuring the CWT amplitudes at 231.1 and 291.0 nm in the HAAR-CWT spectra and at 228.5 and 246.8 nm in BIOR1.5-CWT spectra, respectively. In order to compare the performance of HAAR-CWT and BIOR1.5-CWT approaches, derivative spectrophotometric (DS) method and HPLC as comparison methods, were applied to the PER-IND samples. In this DS method, first derivative absorbance values at 221.6 for PER and 282.7 nm for IND were used to obtain the calibration graphs. The validation of the CWT and DS signal processing methods was carried out by using the recovery study and standard addition technique. In the following step, these methods were successfully applied to the commercial tablets containing PER and IND compounds and good accuracy and precision were reported for the experimental results obtained by all proposed signal processing methods.

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Simple and sensitive procedures for the extraction/preconcentration of molybdenum based on vortex-assisted solidified floating organic drop microextraction (VA-SFODME) and cloud point combined with flame absorption atomic spectrometry (FAAS) and discrete nebulization were developed. The influence of the discrete nebulization on the sensitivity of the molybdenum preconcentration processes was studied. An injection volume of 200 µL resulted in a lower relative standard deviation with both preconcentration procedures. Enrichment factors of 31 and 67 and limits of detection of 25 and 5 µg L-1 were obtained for cloud point and VA-SFODME, respectively. The developed procedures were applied to the determination of Mo in mineral water and multivitamin samples.

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In this study, hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used to classify blends produced from diesel S500 and different kinds of biodiesel produced by the TDSP methodology. The different kinds of biodiesel studied in this work were produced from three raw materials: soybean oil, waste cooking oil and hydrogenated vegetable oil. Methylic and ethylic routes were employed for the production of biodiesel. HCA and PCA were performed on the data from attenuated total reflectance Fourier transform infrared spectroscopy, showing the separation of the blends into groups according to biodiesel content present in the blends and to the kind of biodiesel used to form the mixtures.

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O gene Sw-5 do tomateiro confere resistência a várias espécies de tospovírus e codifica uma proteína contendo domínios de ligação a nucleotídeos e repetições ricas em leucina. Tomateiros com Sw-5 exibem reações necróticas nas folhas inoculadas com tospovírus. Estas reações e a estrutura da proteína Sw-5 indicam que a resistência ocorre por meio do reconhecimento do patógeno e desencadeamento da resposta de hipersensibilidade. A capacidade de Sw-5 de conferir resistência a tospovírus em tabaco selvagem (Nicotiana benthamiana Domin.) foi avaliada em plantas transgênicas. Uma construção com a seqüência aberta de leitura de Sw-5 e sua região 3’ não-traduzida sob controle do promotor 35S do CaMV foi utilizada para transformação de N. benthamiana via Agrobacterium tumefaciens. Plantas de progênies R1 foram inoculadas com um isolado de tospovírus e avaliadas quanto à ocorrência de reação de hipersensibilidade e resistência à infecção sistêmica. Em uma progênie com segregação 3:1 (resistente:suscetível), foi selecionada uma planta homozigota e sua progênie avaliada quanto ao espectro da resistência a tospovírus. Plantas com o transgene exibiram resposta de hipersensibilidade 48 h após a inoculação, sendo resistentes à infecção sistêmica. O fenótipo da resistência foi dependente do isolado viral e um isolado de Tomato chlorotic spot virus (TCSV) causou necrose sistêmica em todas as plantas inoculadas, enquanto que isolados de Groundnut ringspot virus (GRSV) e um isolado relacionado a Chrysanthemum stem necrosis virus (CSNV) ficaram restritos ao sítio de infecção. Comparações do espectro da resistência obtido neste trabalho com aquele observado em outros membros da família Solanaceae indicam que as vias de transdução de sinais e as respostas de defesa ativadas por Sw-5 são conservadas dentro desta família e polimorfismos genéticos nas vias de transdução de sinais ou em componentes das respostas de defesa podem resultar em diferentes níveis de resistência.

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RESUMO As imagens do sensor MODIS fornecem dados que cobrem áreas de grande extensão com alta periodicidade, características fundamentais que possibilitam o monitoramento de culturas agrícolas estratégicas para o Brasil, como as da cana-de-açúcar. Técnicas matemáticas vêm sendo empregadas no estudo de longas séries temporais de índices de vegetação, baseado nas mudanças que acontecem na superfície terrestre, o que facilita o entendimento da dinâmica temporal. O objetivo deste trabalho foi realizar a avaliação da dinâmica do cultivo da cana-de-açúcar no Estado de São Paulo por meio de perfis temporais de dados MODIS, ao longo das safras de 2004/2005 a 2011/2012. A Transformada de Wavelet Daubechies 8 aplicada à série temporal do EVI2 do MODIS mostrou ser uma técnica robusta, pois conseguiu eliminar os ruídos, propiciando, assim, melhor captura das tendências dos ciclos de desenvolvimento da cana-de-açúcar em toda a série temporal. Os perfis temporais suavizados do EVI2 puderam ser utilizados no monitoramento do cultivo da cana-de-açúcar para identificar as épocas de mudanças do uso do solo e da cobertura da terra, acompanhando as variações sazonais dos ciclos fenológicos desde o plantio ou rebrota das soqueiras até à colheita.

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The aim of the present study was to develop a classifier able to discriminate between healthy controls and dyspeptic patients by analysis of their electrogastrograms. Fifty-six electrogastrograms were analyzed, corresponding to 42 dyspeptic patients and 14 healthy controls. The original signals were subsampled, filtered and divided into the pre-, post-, and prandial stages. A time-frequency transformation based on wavelets was used to extract the signal characteristics, and a special selection procedure based on correlation was used to reduce their number. The analysis was carried out by evaluating different neural network structures to classify the wavelet coefficients into two groups (healthy subjects and dyspeptic patients). The optimization process of the classifier led to a linear model. A dimension reduction that resulted in only 25% of uncorrelated electrogastrogram characteristics gave 24 inputs for the classifier. The prandial stage gave the most significant results. Under these conditions, the classifier achieved 78.6% sensitivity, 92.9% specificity, and an error of 17.9 ± 6% (with a 95% confidence level). These data show that it is possible to establish significant differences between patients and normal controls when time-frequency characteristics are extracted from an electrogastrogram, with an adequate component reduction, outperforming the results obtained with classical Fourier analysis. These findings can contribute to increasing our understanding of the pathophysiological mechanisms involved in functional dyspepsia and perhaps to improving the pharmacological treatment of functional dyspeptic patients.

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Tesis (Maestría en Ciencias de la Ingeniería Eléctrica con Orientación en Sistemas Eléctricos de Potencia) UANL, 2010.

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Tesis (Maestro en Ingeniería Eléctrica con Orientación en Potencia) UANL, 2011.

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Tesis (Maestro en Ciencias de la Ingeniería Eléctrica con Orientación en Sistemas Eléctricos de Potencia) UANL, 2011.

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Tesis (Doctor en Ingeniería Eléctrica) UANL, 2011.

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A method for computer- aided diagnosis of micro calcification clusters in mammograms images presented . Micro calcification clus.eni which are an early sign of bread cancer appear as isolated bright spots in mammograms. Therefore they correspond to local maxima of the image. The local maxima of the image is lint detected and they are ranked according to it higher-order statistical test performed over the sub band domain data

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Speech signals are one of the most important means of communication among the human beings. In this paper, a comparative study of two feature extraction techniques are carried out for recognizing speaker independent spoken isolated words. First one is a hybrid approach with Linear Predictive Coding (LPC) and Artificial Neural Networks (ANN) and the second method uses a combination of Wavelet Packet Decomposition (WPD) and Artificial Neural Networks. Voice signals are sampled directly from the microphone and then they are processed using these two techniques for extracting the features. Words from Malayalam, one of the four major Dravidian languages of southern India are chosen for recognition. Training, testing and pattern recognition are performed using Artificial Neural Networks. Back propagation method is used to train the ANN. The proposed method is implemented for 50 speakers uttering 20 isolated words each. Both the methods produce good recognition accuracy. But Wavelet Packet Decomposition is found to be more suitable for recognizing speech because of its multi-resolution characteristics and efficient time frequency localizations