Global ETD Search

341	Contribution à la théorie des ondelettes : application à la turbulence des plasmas de bord de Tokamak et à la mesure dimensionnelle de cibles / Contribution to the wavelet theory : Application to edge plasma turbulence in tokamaks and to dimensional measurement of targets Scipioni, Angel 19 November 2010 (has links) La nécessaire représentation en échelle du monde nous amène à expliquer pourquoi la théorie des ondelettes en constitue le formalisme le mieux adapté. Ses performances sont comparées à d'autres outils : la méthode des étendues normalisées (R/S) et la méthode par décomposition empirique modale (EMD).La grande diversité des bases analysantes de la théorie des ondelettes nous conduit à proposer une approche à caractère morphologique de l'analyse. L'exposé est organisé en trois parties.Le premier chapitre est dédié aux éléments constitutifs de la théorie des ondelettes. Un lien surprenant est établi entre la notion de récurrence et l'analyse en échelle (polynômes de Daubechies) via le triangle de Pascal. Une expression analytique générale des coefficients des filtres de Daubechies à partir des racines des polynômes est ensuite proposée.Le deuxième chapitre constitue le premier domaine d'application. Il concerne les plasmas de bord des réacteurs de fusion de type tokamak. Nous exposons comment, pour la première fois sur des signaux expérimentaux, le coefficient de Hurst a pu être mesuré à partir d'un estimateur des moindres carrés à ondelettes. Nous détaillons ensuite, à partir de processus de type mouvement brownien fractionnaire (fBm), la manière dont nous avons établi un modèle (de synthèse) original reproduisant parfaitement la statistique mixte fBm et fGn qui caractérise un plasma de bord. Enfin, nous explicitons les raisons nous ayant amené à constater l'absence de lien existant entre des valeurs élevées du coefficient d'Hurst et de supposées longues corrélations.Le troisième chapitre est relatif au second domaine d'application. Il a été l'occasion de mettre en évidence comment le bien-fondé d'une approche morphologique couplée à une analyse en échelle nous ont permis d'extraire l'information relative à la taille, dans un écho rétrodiffusé d'une cible immergée et insonifiée par une onde ultrasonore / The necessary scale-based representation of the world leads us to explain why the wavelet theory is the best suited formalism. Its performances are compared to other tools: R/S analysis and empirical modal decomposition method (EMD). The great diversity of analyzing bases of wavelet theory leads us to propose a morphological approach of the analysis. The study is organized into three parts. The first chapter is dedicated to the constituent elements of wavelet theory. Then we will show the surprising link existing between recurrence concept and scale analysis (Daubechies polynomials) by using Pascal's triangle. A general analytical expression of Daubechies' filter coefficients is then proposed from the polynomial roots. The second chapter is the first application domain. It involves edge plasmas of tokamak fusion reactors. We will describe how, for the first time on experimental signals, the Hurst coefficient has been measured by a wavelet-based estimator. We will detail from fbm-like processes (fractional Brownian motion), how we have established an original model perfectly reproducing fBm and fGn joint statistics that characterizes magnetized plasmas. Finally, we will point out the reasons that show the lack of link between high values of the Hurst coefficient and possible long correlations. The third chapter is dedicated to the second application domain which is relative to the backscattered echo analysis of an immersed target insonified by an ultrasonic plane wave. We will explain how a morphological approach associated to a scale analysis can extract the diameter information Ondelettes Principe d'incertitude de Heisenberg Pavage temps-Fréquence Moments Régularité Support compact Fonction d'échelle Fonction d'ondelette Approximations Détails Résolution Filtre QMF Coefficients de Daubechies Analyse Reconstruction Précurseur Algorithme de Mallat Convolution Décimation Symétrisation Orthogonalisation Gram Schmidt Filtres frontières Complexité Décomposition modale empirique Méthode R/S Analyse des fluctuations redressées Fractal Auto-Similarité Plasma Bruit Gaussien fractionnaire Mouvement Brownien fractionnaire Ultrason Wavelets Heisenberg uncertainty principle Time-Frequency tiles Vanishing moments Regularity Compact support Scaling function Wavelet function Approximations Details Resolution QMF filters Daubechies coefficients Analysis Reconstruction Precursor Mallat algorithm Convolution Decimation Mirroring Orthogonalization Gram Schmidt Boundary filters Complexity Empirical Modal Decomposition R/S method Detrended fluctuations Analysis Fractal Self-Similarity Plasma Fractional Gaussian noise Fractional Brownian motion Ultrasound 530.44 515.243 3
342	Análise de carteiras em tempo discreto / Discrete time portfolio analysis Fernando Hideki Kato 14 April 2004 (has links) Nesta dissertação, o modelo de seleção de carteiras de Markowitz será estendido com uma análise em tempo discreto e hipóteses mais realísticas. Um produto tensorial finito de densidades Erlang será usado para aproximar a densidade de probabilidade multivariada dos retornos discretos uniperiódicos de ativos dependentes. A Erlang é um caso particular da distribuição Gama. Uma mistura finita pode gerar densidades multimodais não-simétricas e o produto tensorial generaliza este conceito para dimensões maiores. Assumindo que a densidade multivariada foi independente e identicamente distribuída (i.i.d.) no passado, a aproximação pode ser calibrada com dados históricos usando o critério da máxima verossimilhança. Este é um problema de otimização em larga escala, mas com uma estrutura especial. Assumindo que esta densidade multivariada será i.i.d. no futuro, então a densidade dos retornos discretos de uma carteira de ativos com pesos não-negativos será uma mistura finita de densidades Erlang. O risco será calculado com a medida Downside Risk, que é convexa para determinados parâmetros, não é baseada em quantis, não causa a subestimação do risco e torna os problemas de otimização uni e multiperiódico convexos. O retorno discreto é uma variável aleatória multiplicativa ao longo do tempo. A distribuição multiperiódica dos retornos discretos de uma seqüência de T carteiras será uma mistura finita de distribuições Meijer G. Após uma mudança na medida de probabilidade para a composta média, é possível calcular o risco e o retorno, que levará à fronteira eficiente multiperiódica, na qual cada ponto representa uma ou mais seqüências ordenadas de T carteiras. As carteiras de cada seqüência devem ser calculadas do futuro para o presente, mantendo o retorno esperado no nível desejado, o qual pode ser função do tempo. Uma estratégia de alocação dinâmica de ativos é refazer os cálculos a cada período, usando as novas informações disponíveis. Se o horizonte de tempo tender a infinito, então a fronteira eficiente, na medida de probabilidade composta média, tenderá a um único ponto, dado pela carteira de Kelly, qualquer que seja a medida de risco. Para selecionar um dentre vários modelos de otimização de carteira, é necessário comparar seus desempenhos relativos. A fronteira eficiente de cada modelo deve ser traçada em seu respectivo gráfico. Como os pesos dos ativos das carteiras sobre estas curvas são conhecidos, é possível traçar todas as curvas em um mesmo gráfico. Para um dado retorno esperado, as carteiras eficientes dos modelos podem ser calculadas, e os retornos realizados e suas diferenças ao longo de um backtest podem ser comparados. / In this thesis, Markowitzs portfolio selection model will be extended by means of a discrete time analysis and more realistic hypotheses. A finite tensor product of Erlang densities will be used to approximate the multivariate probability density function of the single-period discrete returns of dependent assets. The Erlang is a particular case of the Gamma distribution. A finite mixture can generate multimodal asymmetric densities and the tensor product generalizes this concept to higher dimensions. Assuming that the multivariate density was independent and identically distributed (i.i.d.) in the past, the approximation can be calibrated with historical data using the maximum likelihood criterion. This is a large-scale optimization problem, but with a special structure. Assuming that this multivariate density will be i.i.d. in the future, then the density of the discrete returns of a portfolio of assets with nonnegative weights will be a finite mixture of Erlang densities. The risk will be calculated with the Downside Risk measure, which is convex for certain parameters, is not based on quantiles, does not cause risk underestimation and makes the single and multiperiod optimization problems convex. The discrete return is a multiplicative random variable along the time. The multiperiod distribution of the discrete returns of a sequence of T portfolios will be a finite mixture of Meijer G distributions. After a change of the distribution to the average compound, it is possible to calculate the risk and the return, which will lead to the multiperiod efficient frontier, where each point represents one or more ordered sequences of T portfolios. The portfolios of each sequence must be calculated from the future to the present, keeping the expected return at the desired level, which can be a function of time. A dynamic asset allocation strategy is to redo the calculations at each period, using new available information. If the time horizon tends to infinite, then the efficient frontier, in the average compound probability measure, will tend to only one point, given by the Kellys portfolio, whatever the risk measure is. To select one among several portfolio optimization models, it is necessary to compare their relative performances. The efficient frontier of each model must be plotted in its respective graph. As the weights of the assets of the portfolios on these curves are known, it is possible to plot all curves in the same graph. For a given expected return, the efficient portfolios of the models can be calculated, and the realized returns and their differences along a backtest can be compared. convexidade convolução aditiva convolução multiplicativa critério de Kelly distribuição Gama Generalizada Downside Risk estratégia multiperiódica função Fox H função Meijer G Lower Partial Moment medidas coerentes de risco mistura finita de distribuições Erlang multiperíodo otimização de carteiras otimização em larga escala produto tensorial retornos aditivos e multiplicativos risco de falência seleção de carteiras seleção de modelo transformada de Laplace transformada de Mellin additive and multiplicative returns additive convolution coherent risk measures convexity default risk Downside Risk finite mixture of Erlang distributions Fox H function Generalized Gamma distribution Kellys criterion Laplace transform large-scale optimization Lower Partial Moment Meijer G function Mellin transform model selection multiperiod multiperiodic strategy multiplicative convolution portfolio optimization portfolio selection tensor product
343	Méthodes d'holographie numérique couleur pour la métrologie sans contact en acoustique et mécanique Tankam, Patrice 12 October 2010 (has links) (PDF) Ce travail de thèse propose des méthodes d'holographie numérique couleur pour la mesure sans contact dans le domaine de l'acoustique, de la mécanique du solide et de la mécanique des fluides. Les méthodes développées pourraient répondre à diverses problématiques académiques et industrielles, notamment, la détection de défauts et de fissurations dans des structures composites, l'analyse des déformations et des vibrations dans leurs 3 composantes, le contrôle de surface et de forme ou l'analyse de fluides dans le cas d'écoulements turbulents à mach subsonique et à mach supersonique. Cette thèse est organisée autour de 5 chapitres qui résument les différents axes de travail. Dans un premier temps, nous avons rappelé quelques aspects théoriques de l'holographie numérique et complété la connaissance du processus de formation des images holographiques numériques en proposant une formulation analytique généralisée incluant les courbures des ondes de référence et de reconstruction numérique, ainsi que des phénomènes non linéaires à l'enregistrement. En particulier nous nous sommes intéressés à développer un modèle de formation des images tenant compte de la saturation des pixels du capteur. Nous avons démontré que, bien que le phénomène de saturation soit non linéaire, nous pouvons néanmoins écrire la relation objet-image avec une formulation analytique linéaire utilisant des produits de convolution. L'analyse théorique a été complétée par une étude expérimentale qui a permis de valider l'approche retenue. Le modèle général de reconstruction permet dans un second temps de définir des stratégies pour la reconstruction numérique d'objets étendus encodés dans des hologrammes couleur. L'algorithme doit avoir pour spécificité de conserver l'horizon reconstruit indépendamment de la longueur d'onde d'enregistrement. Dans ce contexte, ce travail nous a conduit à proposer un algorithme de transformée de Fresnel avec zéro-padding dépendant de la longueur d'onde, puis des algorithmes de convolution à balayage spectral et à grandissement variable qui sont basés sur le concept d'adaptation de bande passante spatiale. Par ailleurs, pour les problématiques rencontrées en mécanique des fluides, nous avons adapté une méthode de filtrage par transformée de Fourier à la reconstruction des objets de phase. Ces algorithmes ont été appliqués expérimentalement à des enregistrements monochromes, bi-couleurs et tri chromatiques montrant ainsi leur grande versatilité. Les deux dernières parties de la thèse traitent du développement de dispositifs holographiques numériques à deux et trois longueurs d'onde pour la métrologie sans contact. Le volet expérimental couvre les champs de la mécanique du solide, l'acoustique et la mécanique des fluides. Nous avons développé plusieurs architectures : architectures bi-couleur et tri-couleur à multiplexage spatial des hologrammes, architecture bi-couleur et tri-chromatique à codage par stack de photodiode, architecture tri chromatique à codage par triple capteur. Les deux dernières architectures s'avèrent les plus simples à mettre en oeuvre. Le banc expérimental bi-couleur à multiplexage spatial a été appliqué à des problématiques industrielles et académiques. La première concerne l'identification de causes de fissuration de capacité sur des composants PCB pour l'automobile. Nous avons mis en évidence une anisotropie de contrainte sur la capacité lors de l'encastrement du PCB dans son support, conduisant ainsi à la probable fissuration de l'élément. La seconde application constitue une première tentative de mise en évidence de modes tourbillonnaires dans des milieux granulaires non consolidés. Nous avons développé deux stratégies de détermination du mouvement 3D du milieu à partir de l'enregistrement d'hologrammes bi-couleurs multiplexés spatialement. Les résultats expérimentaux des modes planaires montrent des tourbillons à certaines fréquences d'excitation du milieu. Nos résultats expérimentaux montrent quelques contradictions dont les causes ont été identifiées. Afin de lever toute ambiguïté nous avons développé un banc d'holographie numérique pseudo-pulsée à 3 couleurs permettant la détermination exclusive de chacune des composantes du vecteur déplacement. Dans le cadre d'une collaboration avec l'ONERA (centre de Lille), nous avons développé une méthode d'holographie numérique tri-chromatique pour l'étude d'écoulements tourbillonnaires. La méthode proposée permet la détermination du champ d'indice ou de masse volumique dans un écoulement et, après validation, a été appliquée à plusieurs cas d'écoulements à mach subsonique et à mach supersonique. Les résultats expérimentaux obtenus sont une première démonstration des potentialités d'application de la méthode d'holographie numérique couleur dans le domaine de la mécanique des fluides. Holographie numérique couleur mesure optique contrôle non destructif mesure plein champ diffraction de Fresnel interférences capteur couleur détection multi-chromatique multiplexage spatial transformée de Fresnel convolution grandissement variable interférométrie holographique métrologie multidimensionnelle
344	Multikanálová dekonvoluce obrazů / Multichannel Image Deconvolution Bradáč, Pavel January 2009 (has links) This Master Thesis deals with image restoration using deconvolution. The terms introducing into deconvolution theory like two-dimensional signal, distortion model, noise and convolution are explained in the first part of thesis. The second part deals with deconvolution methods via utilization of the Bayes approach which is based on the probability principle. The third part is focused on the Alternating Minimization Algorithm for Multichannel Blind Deconvolution. At the end this algorithm is written in Matlab with utilization of the NAG C Library. Then comparison of different optimization methods follows (simplex, steepest descent, quasi-Newton), regularization forms (Tichonov, Total Variation) and other parameters used by this deconvolution algorithm.
345	Incorporating Scene Depth in Discriminative Correlation Filters for Visual Tracking Stynsberg, John January 2018 (has links) Visual tracking is a computer vision problem where the task is to follow a targetthrough a video sequence. Tracking has many important real-world applications in several fields such as autonomous vehicles and robot-vision. Since visual tracking does not assume any prior knowledge about the target, it faces different challenges such occlusion, appearance change, background clutter and scale change. In this thesis we try to improve the capabilities of tracking frameworks using discriminative correlation filters by incorporating scene depth information. We utilize scene depth information on three main levels. First, we use raw depth information to segment the target from its surroundings enabling occlusion detection and scale estimation. Second, we investigate different visual features calculated from depth data to decide which features are good at encoding geometric information available solely in depth data. Third, we investigate handling missing data in the depth maps using a modified version of the normalized convolution framework. Finally, we introduce a novel approach for parameter search using genetic algorithms to find the best hyperparameters for our tracking framework. Experiments show that depth data can be used to estimate scale changes and handle occlusions. In addition, visual features calculated from depth are more representative if they were combined with color features. It is also shown that utilizing normalized convolution improves the overall performance in some cases. Lastly, the usage of genetic algorithms for hyperparameter search leads to accuracy gains as well as some insights on the performance of different components within the framework. Tracking Visual Deep Learning Machine Learning CNN Convolutional Neural Network Unsupervised Learning Clustering Genetic Algorithms Features Visual featues Channel Coding RGBD Scene Depth Map Kinect Discriminative Correlation Filters SRDCF DCF Spatial Spatially Regularized Hyperparameter Search Occlusion Detection Handling Kalman Filters Normalized Convolution Bayesian Gaussian Mixture Scale Estimation Conjugate Gradient Linkoping Sweden Visuell Följning Särdrag Djupa Faltningsnätverk Maskininlärning Djup Inlärning Genetiska Algoritmer Klustring Djup RGBD Linköping Sverige
346	Geometric approach to multi-scale 3D gesture comparison Ochoa Mayorga, Victor Manuel 11 1900 (has links) The present dissertation develops an invariant framework for 3D gesture comparison studies. 3D gesture comparison without Lagrangian models is challenging not only because of the lack of prediction provided by physics, but also because of a dual geometry representation, spatial dimensionality and non-linearity associated to 3D-kinematics. In 3D spaces, it is difficult to compare curves without an alignment operator since it is likely that discrete curves are not synchronized and do not share a common point in space. One has to assume that each and every single trajectory in the space is unique. The common answer is to assert the similitude between two or more trajectories as estimating an average distance error from the aligned curves, provided that the alignment operator is found. In order to avoid the alignment problem, the method uses differential geometry for position and orientation curves. Differential geometry not only reduces the spatial dimensionality but also achieves view invariance. However, the nonlinear signatures may be unbounded or singular. Yet, it is shown that pattern recognition between intrinsic signatures using correlations is robust for position and orientation alike. A new mapping for orientation sequences is introduced in order to treat quaternion and Euclidean intrinsic signatures alike. The new mapping projects a 4D-hyper-sphere for orientations onto a 3D-Euclidean volume. The projection uses the quaternion invariant distance to map rotation sequences into 3D-Euclidean curves. However, quaternion spaces are sectional discrete spaces. The significance is that continuous rotation functions can be only approximated for small angles. Rotation sequences with large angle variations can only be interpolated in discrete sections. The current dissertation introduces two multi-scale approaches that improve numerical stability and bound the signal energy content of the intrinsic signatures. The first is a multilevel least squares curve fitting method similar to Haar wavelet. The second is a geodesic distance anisotropic kernel filter. The methodology testing is carried out on 3D-gestures for obstetrics training. The study quantitatively assess the process of skill acquisition and transfer of manipulating obstetric forceps gestures. The results show that the multi-scale correlations with intrinsic signatures track and evaluate gesture differences between experts and trainees. 3D gesture comparison Multiscale curvature Curvature-torsion differential geometry complex trajectories quaternion trajectories quaternion projections quaternion metrics 3D trajectory smoothing curvature signature correlations qualitative skill transfer measure medical manipulative gestures nonlinear signatures anisotropic kernel filter curvature numerical stability quaternion smoothing kinematics motor skill transfer curvature signature torsion signature arc-length parameterization tensors Frenet-Serret quaternion framework nonlinear kernel filter geodesic distance finite difference methods differential convolution filter Savitzky-Golay filter least squares curve fitting curvature neighborhood multilevel curvature analysis medical training child bearing simulator robotic simulator motion tracking 3D electromagnetic trackers sequence comparison medical training
347	Geometric approach to multi-scale 3D gesture comparison Ochoa Mayorga, Victor Manuel Unknown Date No description available. 3D gesture comparison Multiscale curvature Curvature-torsion differential geometry complex trajectories quaternion trajectories quaternion projections quaternion metrics 3D trajectory smoothing curvature signature correlations qualitative skill transfer measure medical manipulative gestures nonlinear signatures anisotropic kernel filter curvature numerical stability quaternion smoothing kinematics motor skill transfer curvature signature torsion signature arc-length parameterization tensors Frenet-Serret quaternion framework nonlinear kernel filter geodesic distance finite difference methods differential convolution filter Savitzky-Golay filter least squares curve fitting curvature neighborhood multilevel curvature analysis medical training child bearing simulator robotic simulator motion tracking 3D electromagnetic trackers sequence comparison medical training
348	Minimization of Noise and Vibration Related to Driveline Imbalance using Robust Design Processes Al-Shubailat, Omar 17 August 2013 (has links) Variation in vehicle noise, vibration and harshness (NVH) response can be caused by variability in design (e.g. tolerance), material, manufacturing, or other sources of variation. Such variation in the vehicle response causes a higher percentage of produced vehicles to have higher levels (out of specifications) of NVH leading to higher number of warranty claims and loss of customer satisfaction, which are proven costly. Measures must be taken to ensure less warranty claims and higher levels of customer satisfactions. As a result, original equipment manufacturers (OEMs) have implemented design for variation in the design process to secure an acceptable (or within specification) response. The focus here will be on aspects of design variations that should be considered in the design process of drivelines. Variations due to imbalance in rotating components can be unavoidable or costly to control. Some of the major components in the vehicle that are known to have imbalance and traditionally cause NVH issues and concerns include the crankshaft, the drivetrain components (transmission, driveline, half shafts, etc.), and wheels. The purpose is to assess NVH as a result of driveline imbalance variations and develop a tool to help design a more robust system to such variations. program. Java quality engineering quality capability studies manufacturing processes manufacturing engineer design engineer sales profit customer concern warranty objectionable Eigen functions vectors Eigen Eigen values identity Euler differential equations differential transfer case shaft driveline static imbalance dynamic imbalance passenger customer driver inboard ear driver outboard ear steering wheel seat track variation Gamma distribution normal distribution standard deviation average variance mean phasor victor scalar linear system LTI linear time invariant transfer function output input microphone accelerometers tachometer channels order frequency frequency domain time domain convolution Transformation Fourier Transformer Fourier imaginary and real logarithmic decibel sensitivity curves run down run up two wheel drive Four Wheel Drive Nissan Truck OEM Original Equipment Manufacturers Data Acquisitions Channels Simulation Six Sigma variability Design Robust sensitivity Vibration Imbalance Noise Harshness NVH Driveline
349	Channel Probing for an Indoor Wireless Communications Channel Hunter, Brandon 13 March 2003 (has links) (PDF) The statistics of the amplitude, time and angle of arrival of multipaths in an indoor environment are all necessary components of multipath models used to simulate the performance of spatial diversity in receive antenna configurations. The model presented by Saleh and Valenzuela, was added to by Spencer et. al., and included all three of these parameters for a 7 GHz channel. A system was built to measure these multipath parameters at 2.4 GHz for multiple locations in an indoor environment. Another system was built to measure the angle of transmission for a 6 GHz channel. The addition of this parameter allows spatial diversity at the transmitter along with the receiver to be simulated. The process of going from raw measurement data to discrete arrivals and then to clustered arrivals is analyzed. Many possible errors associated with discrete arrival processing are discussed along with possible solutions. Four clustering methods are compared and their relative strengths and weaknesses are pointed out. The effects that errors in the clustering process have on parameter estimation and model performance are also simulated. multipath multipath propagation propagation environment indoor propagation indoor multipath indoor multipath propagation channel probing channel probing indoor wireless communications channel indoor wireless communications indoor wireless communications wireless communications wireless communications channel MIMO SISO multiple input multiple output single input single output antenna diversity antenna diversity antenna array channel modeling modeling model wireless propagation clustering methods clustering algorithms clustering parameter estimation parameter channel matrix h matrix ray tracing point spread function psf deconvolution clean algorithm clean algorithm antenna pattern network analyzer temporal pattern 2.4 ghz system 6 ghz system channel capacity capacity estimate channel capacity estimate propagation environment scattering transfer matrix matrix water filling solution water filling method water filling Saleh Valenzuela Saleh and Valenzuela Model arrival time of arrival angle of arrival direction of arrival arrival amplitude arrivals antenna positioner data simulations measurements angle of departure direction of departure correlation convolution errors error CFA CFAD constant false alarm constant false alarm detection signal signal dependent clutter clutter returns transmitter transmit receive receiver transmit antenna receive antenna spatial correlation system PSF system point spread function mapping fuzzy c-means clustering fuzzy clustering c-means clustering c-means fuzzy k-means euclidean distance time amplitude delay performance prediction performance prediction errors fuzzy weighted distance method rectangular method weighted rectangular method statistics statistical statistical model Electrical and Computer Engineering

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