Cette thèse porte sur le contrôle non destructif par ultrasons et la détection de défauts dans des matériaux complexes. Elle apporte des améliorations à l’imagerie Total Focusing Method(TFM) lorsque les images sont altérées par un haut niveau de bruit. Trois points essentiels sont abordés : l’optimisation de l’acquisition de la matrice des réponses impulsionnelles K(t) avec des sources virtuelles ou des émissions codées en amplitude ; la séparation des sous-espaces vectoriels associés au signal et au bruit avec la Décomposition de l’Opérateur de Retournement Temporel (DORT) ; et la formation d’image dans le domaine temporel avec TFM après le débruitage des signaux. La thèse s’intéresse au bruit cohérent lié à la structure hétérogène d’un acier à gros grains, puis au bruit électronique incohérent introduit par la chaîne d’acquisition des signaux dans le cas d’un matériau viscoélastique très atténuant. Ce travail s’intéresse aussi aux artefacts d’imagerie engendrés par les ondes de surface se propageant le long d’un capteur multiéléments au contact. Les valeurs singulières associées à ces modes guidés sont modélisées pour faciliter l’interprétation de la décomposition de la matrice de transfert Kˆ(f)et filtrer les artefacts d’imagerie. Lorsque la zone d’intérêt est éloignée de l’axe central du capteur,une approche alternative à la rétro-propagation de vecteurs singuliers est proposée pour améliorer la qualité des images formées dans le domaine fréquentiel. Elle consiste à combinerla méthode DORT avec l’imagerie topologique. Après filtrage du bruit et des ondes de surface,les images TFM sont comparées avec celles calculées par rétro-propagation ou par imagerie topologique. Ensuite, ce travail s’intéresse à la détection dans un tube en polyéthylène dont l’atténuation viscoélastique fait apparaître un fort bruit électronique sur les images TFM. Pour enregistrer la matrice K(t) en augmentant la profondeur de pénétration des ultrasons, deux pseudo-codages de Hadamard sont développés, et les gains apportés sont justifiés théoriquement et expérimentalement. Un modèle théorique des valeurs singulières associées au bruit est ensuite proposé pour faciliter l’extraction de la réponse du défaut dans la matrice Kˆ(f). Enfin, la thèse introduit une méthode de filtrage pour Plane Wave Imaging (PWI) offrant de bonnes performances dans les matériaux complexes car elle cumule les avantages de sources virtuelles (utilisées dans l’acier) et des émissions codées (utilisées dans le polyéthylène) / This thesis is related to ultrasonic non-destructive testing and detection of defects in complex materials. Improvements of the Total Focusing Method (TFM) when images are corrupted bya high noise level are proposed. Three main points are developed : the optimization of the acquisition of the impulse response matrix K(t) using virtual sources or spatial coding ; the separation of subspaces associated with the signal and the noise using the decomposition of the time reversal operator (DORT) ; and the image formation in the time domain with TFM after the signal denoising. Two different types of noise are considered : the coherent noise linked to the heterogeneous structure of a coarse-grained steel, and the incoherent electronic noise introduced by the signal acquisition system in the case of a high attenuating viscoelastic material.The study also focuses on imaging artifacts generated by surface waves which propagate alonga contact array probe. The singular values associated with these guided modes are modeled tofacilitate the interpretation of the decomposition of the transfer matrix ˆK( f ), and to filter theartifacts. When the region of interest is far from the probe axis, an alternative approach to singular vector back-propagation is proposed in order to improve the quality of images formedin the frequency domain. This approach consists in combining the DORT method with the topologica limaging. After the noise and surface waves filtering, the TFM images are comparedwith those calculated by the singular vector back-propagation or by the topological imaging.Then, this work focuses on the detection in a polyethylene pipe of high viscoelastic attenuation introducing unwanted noise in the TFM images. To record the K(t) matrix while increasingthe ultrasonic penetration depth, two Hadamard pseudo-codes are developed, and the gainsare theoretically and experimentally justified. A theoretical model of the singular values associated with the noise is then proposed to facilitate the defect response extraction from thetransfer matrix ˆK( f ). Finally, a filtering procedure for Plane Wave Imaging (PWI) is proposed,which combines the advantages of virtual sources (used in the coarse-grained steel) and coded transmissions (used in the polyethylene), thus giving excellent performances in complex materials

In this dissertation I investigated a multi-channel and multi-bit rate all-optical clock recovery device. This device, a birefringent Fabry-Perot resonator, had previously been demonstrated to simultaneously recover the clock signal from 10 wavelength channels operating at 10 Gb/s and one channel at 40 Gb/s. Similar to clock signals recovered from a conventional Fabry-Perot resonator, the clock signal from the birefringent resonator suffers from a bit pattern effect. I investigated this bit pattern effect for birefringent resonators numerically and experimentally and found that the bit pattern effect is less prominent than for clock signals from a conventional Fabry-Perot resonator.I also demonstrated photonic balancing which is an all-optical alternative to electrical balanced detection for phase shift keyed signals. An RZ-DPSK data signal was demodulated using a delay interferometer. The two logically opposite outputs from the delay interferometer then counter-propagated in a saturated SOA. This process created a differential signal which used all the signal power present in two consecutive symbols. I showed that this scheme could provide an optical alternative to electrical balanced detection by reducing the required OSNR by 3 dB.I also show how this method can provide amplitude regeneration to a signal after modulation format conversion. In this case an RZ-DPSK signal was converted to an amplitude modulation signal by the delay interferometer. The resulting amplitude modulated signal is degraded by both the amplitude noise and the phase noise of the original signal. The two logically opposite outputs from the delay interferometer again counter-propagated in a saturated SOA. Through limiting amplification and noise modulation this scheme provided amplitude regeneration and improved the Q-factor of the demodulated signal by 3.5 dB.Finally I investigated how SPM provided by the SOA can provide a method to reduce the in-band noise of a communication signal. The marks, which represented data, experienced a spectral shift due to SPM while the spaces, which consisted of noise, did not. A bandpass filter placed after the SOA then selected the signal and filtered out what was originally in-band noise. The receiver sensitivity was improved by 3 dB.

The aim was to test the methods for suppression 50 Hz noise with adaptive filtering. When using the general scheme of adaptive and deterministic scheme to suppress hum. The work is a theoretical derivation of adaptive algorithms and some examples of modeling in MATLAB.

No description available.

Esse trabalho apresenta uma nova proposta do algoritmo de médias não-locais (NLM - Non-Local Means) para a filtragem do ruído quântico de imagens mamográficas digitais adquiridas com dose de radiação reduzida. A redução nas doses de radiação tem como objetivo principal minimizar os riscos de indução ao câncer de mama causado pela exposição do paciente à radiação ionizante no momento do exame. No entanto, a qualidade da imagem mamográfica diminui com a redução da dose de radiação e o ruído predominante nesse caso é o ruído quântico, que segue a distribuição de Poisson e é dependente do sinal. Como o algoritmo NLM foi originalmente desenvolvido para filtragem de ruído Gaussiano independente do sinal, a proposta desse trabalho foi de adaptar o algoritmo NLM original de modo que ele se tornasse mais adequado para filtragem do ruído encontrado nas imagens mamográficas digitais. Nessa nova abordagem, chamada de Variance Map Non-local Means (VM-NLM), a filtragem do ruído quântico é realizada no próprio domínio da imagem, levando-se em conta a variância do ruído em cada pixel da imagem, já que o ruído é dependente do sinal. Com isso, elimina-se a necessidade de realizar uma estimativa precisa dos parâmetros do ruído para o uso de uma transformada de estabilização de variância (como a transformada generalizada de Anscombe), antes do processo de filtragem. Essa estimativa normalmente requer medidas preliminares no equipamento mamográfico, cujo acesso nem sempre é viável na prática. A proposta foi avaliada em três bancos de imagens mamográficas adquiridas com diferentes doses de radiação. As avaliações de desempenho foram realizadas comparando objetivamente a qualidade das imagens mamográficas obtidas com a dose padrão de radiação com as adquiridas com doses reduzidas, após a filtragem do ruído. Os resultados obtidos com o algoritmo proposto mostraram que ele produz imagens mamográficas mais nítidas e com melhor preservação de bordas e pequenos detalhes do que o algoritmo NLM original. / This work presents a new proposal from the non-local means algorithm (NLM - Non-Local Means) for filtering the quantum noise of digital mammography images acquired with reduced radiation dose. The reduction in radiation doses aims to minimize the risk of inducing breast cancer caused by patient exposure to ionizing radiation during the examination. However, the mammographic image quality decreases with the reduction of the radiation dose and the predominant noise in this case is the quantum noise, which follows the Poisson distribution and it is dependent of the signal. As the NLM algorithm was originally developed for filtering additive Gaussian noise, the purpose of this study was to adapt the original NLM algorithm so that it becomes more suitable for filtering the noise found in digital mammographic images. In this new approach, called Variance Map Non-local Means (VM-NLM), the filtering of the quantum noise is performed in the image domain, considering the noise variance in each pixel of the image, since the noise depends on the pixel value. Thus, it eliminates the need for an accurate estimate of the noise parameters for the use of a variance stabilization transform (such as generalized Anscombe Transformation) before the filtering process. This estimate typically requires preliminary measurements in the mammographic equipment, which is not always viable in clinical practice. The proposal was evaluated in three databases of mammographic images acquired with different radiation doses. Performance evaluations were conducted comparing objectively the quality of mammographic images acquired with standard radiation dose and with reduced doses, after filtering the noise. The results obtained with the proposed algorithm showed that it produces sharper mammographic images with better preservation of edges and small details than the original NLM algorithm.

Esse trabalho apresenta uma nova proposta do algoritmo de médias não-locais (NLM - Non-Local Means) para a filtragem do ruído quântico de imagens mamográficas digitais adquiridas com dose de radiação reduzida. A redução nas doses de radiação tem como objetivo principal minimizar os riscos de indução ao câncer de mama causado pela exposição do paciente à radiação ionizante no momento do exame. No entanto, a qualidade da imagem mamográfica diminui com a redução da dose de radiação e o ruído predominante nesse caso é o ruído quântico, que segue a distribuição de Poisson e é dependente do sinal. Como o algoritmo NLM foi originalmente desenvolvido para filtragem de ruído Gaussiano independente do sinal, a proposta desse trabalho foi de adaptar o algoritmo NLM original de modo que ele se tornasse mais adequado para filtragem do ruído encontrado nas imagens mamográficas digitais. Nessa nova abordagem, chamada de Variance Map Non-local Means (VM-NLM), a filtragem do ruído quântico é realizada no próprio domínio da imagem, levando-se em conta a variância do ruído em cada pixel da imagem, já que o ruído é dependente do sinal. Com isso, elimina-se a necessidade de realizar uma estimativa precisa dos parâmetros do ruído para o uso de uma transformada de estabilização de variância (como a transformada generalizada de Anscombe), antes do processo de filtragem. Essa estimativa normalmente requer medidas preliminares no equipamento mamográfico, cujo acesso nem sempre é viável na prática. A proposta foi avaliada em três bancos de imagens mamográficas adquiridas com diferentes doses de radiação. As avaliações de desempenho foram realizadas comparando objetivamente a qualidade das imagens mamográficas obtidas com a dose padrão de radiação com as adquiridas com doses reduzidas, após a filtragem do ruído. Os resultados obtidos com o algoritmo proposto mostraram que ele produz imagens mamográficas mais nítidas e com melhor preservação de bordas e pequenos detalhes do que o algoritmo NLM original. / This work presents a new proposal from the non-local means algorithm (NLM - Non-Local Means) for filtering the quantum noise of digital mammography images acquired with reduced radiation dose. The reduction in radiation doses aims to minimize the risk of inducing breast cancer caused by patient exposure to ionizing radiation during the examination. However, the mammographic image quality decreases with the reduction of the radiation dose and the predominant noise in this case is the quantum noise, which follows the Poisson distribution and it is dependent of the signal. As the NLM algorithm was originally developed for filtering additive Gaussian noise, the purpose of this study was to adapt the original NLM algorithm so that it becomes more suitable for filtering the noise found in digital mammographic images. In this new approach, called Variance Map Non-local Means (VM-NLM), the filtering of the quantum noise is performed in the image domain, considering the noise variance in each pixel of the image, since the noise depends on the pixel value. Thus, it eliminates the need for an accurate estimate of the noise parameters for the use of a variance stabilization transform (such as generalized Anscombe Transformation) before the filtering process. This estimate typically requires preliminary measurements in the mammographic equipment, which is not always viable in clinical practice. The proposal was evaluated in three databases of mammographic images acquired with different radiation doses. Performance evaluations were conducted comparing objectively the quality of mammographic images acquired with standard radiation dose and with reduced doses, after filtering the noise. The results obtained with the proposed algorithm showed that it produces sharper mammographic images with better preservation of edges and small details than the original NLM algorithm.

Los Radares de Apertura Sintética, o sistemas SAR, representan el mejorejemplo de sistemas activos de teledetección por microondas. Debido a su naturaleza coherente, un sistema SAR es capaz de adquirir información dedispersión electromagnética con una alta resolución espacial, pero por otro lado, esta naturaleza coherente provoca también la aparición de speckle.A pesar de que el speckle es una medida electromagnética, sólo puede ser analizada como una componente de ruido debido a la complejidad asociadacon el proceso de dispersión electromagnética.Para eliminar los efectos del ruido speckle adecuadamente, es necesario un modelo de ruido, capaz de identificar las fuentes de ruido y como éstasdegradan la información útil. Mientras que este modelo existe para sistemasSAR unidimensionales, conocido como modelo de ruido speckle multiplicativo,éste no existe en el caso de sistemas SAR multidimensionales.El trabajo presentado en esta tesis presenta la definición y completa validación de nuevos modelos de ruido speckle para sistemas SAR multidimensionales,junto con su aplicación para la reducción de ruido speckle y la extracción de información.En esta tesis, los datos SAR multidimensionales, se consideran bajo una formulación basada en la matriz de covarianza, ya que permite el análisisde datos sobre la base del producto complejo Hermítico de pares de imágenesSAR. Debido a que el mantenimiento de la resolución especial es un aspectoimportante del procesado de imágenes SAR, la reducción de ruido speckleestá basada, en este trabajo, en la teoría de análisis wavelet.

[pt] As RNA Temporais, em função de sua estrutura, consideram o tempo na sua operação, incorporando memória de curto prazo distribuída na rede em todos os neurônios escondidos e em alguns dos casos nos neurônios de saída. Esta classe de redes é utilizada para representar melhor a natureza temporal dos sistemas dinâmicos. Em contraste, a RNA estática tem uma estrutura apropriada para tarefas de reconhecimento de padrões, classificação e outras de natureza estática ou estacionária tendo sido utilizada com sucesso em diversas aplicações. O objetivo desta tese, portanto foi estudar a teoria e avaliar o desempenho das Redes Neurais Temporais em comparação com as Redes Neurais Estáticas, em aplicações de sistemas dinâmicos. O desenvolvimento desta pesquisa envolveu 3 etapas principais: pesquisa bibliográfica das metodologias desenvolvidas para RNA Temporais; seleção e implementação de modelos para a avaliação destas redes; e estudo de casos. A pesquisa bibliográfica permitiu compila e classificar os principais trabalhos sobre RNA Temporais. Tipicamente, estas redes podem ser classificadas em dois grupos: Redes com Atraso no Tempo e Redes Recorrentes. Para a análise de desempenho, selecionou-se uma redee de cada grupo para implementação. Do primeiro grupo foi selecionada a Rede FIR, onde as sinapses são filtros FIR (Finite-duration Impulse Response) que representam a natureza temporal do problema. A rede FIR foi selecionada por englobar praticamente, todos os outros métodos de sua classe e apresentar um modelo matemático mais formal. Do segundo grupo, considerou-se a rede recorrente de Elman que apresenta realimentação global de cada um dos neurônios escondidos para todos eles. No estudo de casos testou-se o desempenho das redes selecionadas em duas linhas de aplicação: previsão de séries temporais e processamento digital de sinais. No caso de previsão de séries temporais, foram utilizadas séries de consumo de energia elétrica, comparando-se os resultados com os encontrados na literatura a partir de métodos de Holt-Winters, Box & Jenkins e RNA estáticas. No caso da aplicação das RNA em processamento digital de sinais, utilizou-se a filtragem de ruído em sinais de voz onde foram feitas comparações com os resultados apresentados pelo filtro neural convencional, que é uma rede feed-forward multicamada com o algoritmo de retropropagação para o aprendizado. Este trabalho demonstrou na prática que as RNA temporais conseguem capturar as características dos processos temporais de forma mais eficiente que as RNA Estatísticas e outros métodos tradicionais, podendo aprender diretamente o comportamento não estacionário das séries temporais. Os resultados demonstraram que a rede neural FIR e a rede Elman aprendem melhor a complexidade dos sinais de voz. / [en] This dissertation investigates the development of Artificial Neural Network (ANN) in the solution of problems where the patterns presented to the network have a temporary relationship to each other, such as time series forecast and voice processing. Temporary ANN considers the time in its operation, incorporating memory of short period distributed in the network in all the hidden neurons and in the output neurons in some cases. This class of network in better used to represent the temporary nature of the dynamic systems. In contrast, Static ANN has a structure adapted for tasks of pattern recognition, classification and another static or stationary problems, achieving great success in several applications. Considered an universal approximator, Static ANN has also been used in applications of dynamic systems, through some artifices in the input of the network and through statistical data pre- processings. The objective of this work is, therefore to study the theory and evaluate the performance of Temporal ANN, in comparison with Static ANN, in applications of dynamics systems. The development of this research involved 3 main stages: bibliographical research of the methodologies developed for Temporal ANN; selection and implementation of the models for the evaluation of these networks; and case studies. The bibliographical research allowed to compile and to classify the main on Temporal ANN, Typically, these network was selected, where the synapses are filters FIR (Finite-duration Impulse Response) that represent the temporary nature of the problem. The FIR network has been selected since it includes practically all other methods of its class, presenting a more formal mathematical model. On the second group, the Elman recurrent network was considered, that presents global feedback of each neuron in the hidden layer to all other neurons in this layer. In the case studies the network selected have been tested in two application: forecast of time series and digital signal processing. In the case of forecast, result of electric energy consumption time series prediction were compared with the result found in the literature such as Holt-Winters, Box & Jenkins and Static ANN methods. In the case of the application of processing where the comparisons were made with the results presented by the standard neural filter, made of a multilayer feed-forward network with the back propagation learning algorithm. This work showed in practice that Temporal ANN captures the characteristics of the temporary processes in a more efficient way that Static ANN and other methods, being able to learn the non stationary behavior of the temporary series directly. The results showed that the FIR neural network and de Elman network learned better the complexity of the voice signals.

Made available in DSpace on 2015-04-11T14:03:17Z (GMT). No. of bitstreams: 1 DISSERTACAO ADRIANO NOGUEIRA.pdf: 382280 bytes, checksum: fc1f9e0caac3d97ff74a893e97298a71 (MD5) Previous issue date: 2008-12-17 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Digital processing of speech signal is applied in several computer applications, which the major ones are the following: Recognition, synthesis and coding of speech. All these applications require the amount of data in the acoustic signal to be reduced, in order to allow processing by a computer device. The feature extraction of speech signal, that is the goal of this study, performs this action. The features extracted should well depict the speech signal and should have no redundancy, in order to increase the performance of the systems using them. The feature extraction Mel Frequency Cepstral Coefficients (MFCC) method partially fulfills these requirements, but it is seriously damaged when noise signal is acting. The appliance of the statistical method of Factorial Analysis is intended to filter the noise components from the speech. The results of the experiments performed in this work shows that this is a competitive method, especially when used to generate acoustic models in severe noise conditions. / O processamento digital do sinal de voz é empregado em diversas aplicações computacionais, das quais as principais são: Reconhecimento, síntese e codificação da fala. Todas estas aplicações requerem que ocorra redução da quantidade de informações da onda acústica, de maneira a permitir o processamento por um computador. O processo de extração de características do sinal de voz, objeto de estudo deste trabalho, realiza esta tarefa. As características extraídas devem caracterizar o sinal de voz e não conter redundância, de forma a maximizar o desempenho dos sistemas que as utilizem. O método MFCC (Mel Frequency Cepstral Coefficients) de extração de características cumpre parcialmente esses requisitos, mas é seriamente degradado sob a incidência de ruído. A aplicação do método estatístico de Análise Fatorial objetiva filtrar o sinal de ruído das locuções. Os resultados obtidos dos experimentos realizados indicam a competitividade deste método, especialmente quando usado na geração dos modelos acústicos robustos em condições de ruído severo.

This thesis is focused on the compression algorithm's analysis of MJPEG format and its implementation in FPGA chip. Three additional video bitstream reduction methods have been evaluated for real-time low latency applications of MJPEG format. These methods are noise filtering, inter-frame encoding and lowering video's quality. Based on this analysis, a MJPEG codec has been designed for implementation into FPGA chip XC6SLX45, from Spartan-6 family.