Made available in DSpace on 2016-08-17T14:52:50Z (GMT). No. of bitstreams: 1 Ewaldo Eder.pdf: 1808292 bytes, checksum: 65e8f3c3afbcf9e5bfd61e1b73fb305f (MD5) Previous issue date: 2006-02-17 / In this work we develop a family of adaptive algorithms based on nonlinear functions as a criterion to be applied upon the error, that we want to minimize. Such a development is based upon the use of high order statistics to obtain additional information of the signals involved in the process, intending to enhance the adaptive filtering performance. We derive equations based upon the Taylor s series expansion of the nonlinear functions in order to obtain criterions that guarantee convergence. We also make a study about the covariance of the weight vector on steady state and determine equations that measure the time constant of the adaptive process. We present the sigmoidal algorithm that uses the function Ln(cosh ") as criterion. Simulations of this algorithm are performed to validate the theory and it is also applied to obtain the deterministic components of real impedance cardiographic signals. / Neste trabalho é desenvolvida uma famılia de algoritmos adaptativos baseados em funções não lineares como critério a ser aplicado sobre o erro, o qual deseja-se minimizar. Tal desenvolvimento baseia-se na utilização de estatısticas de alta ordem para a obtenção de mais informações sobre os sinais envolvidos no processo, com o objetivo de melhorar a performance de um filtro adaptativo. Derivamos equações, baseadas na expansão em séries de Taylor das funções não lineares, para a obtenção de critérios que garantam a convergência. Também fazemos um estudo da covariância do vetor peso em regime estacionário e determinamos equações que mensurem a constante de tempo do processo adaptativo. Apresentamos o algoritmo sigmoidal, que utiliza como critério a função Ln(cosh "). Foram feitas simulações com este algoritmo para validar a teoria apresentada, e também o aplicamos para a obtenção das componentes determinısticas de sinais reais de impedância cardiográfica.

Este trabalho tem a finalidade de analisar algumas técnicas de processamento do sinal mioelétrico, de forma a possibilitar uma posterior implementação de um circuito, que reconheça este sinal e apresente como saída um sinal de controle a ser utilizado em sistemas de reabilitação. Foram simuladas e avaliadas três técnicas de filtragem para o sinal mioelétrico, a fim de atenuar a interferência dos principais ruídos que corrompem este sinal. As técnicas avaliadas foram: filtragem digital clássica; cancelamento de ruído adaptativo e reconstrução do sinal por meio das componentes obtidas pela transformada wavelet. Também foi implementado e analisado um sistema simplificado de reconhecimento dos padrões para este sinal, realizado por meio de uma rede neural artificial, em que foi aplicado em sua entrada o próprio sinal mioelétrico e não suas características obtidas por processamentos matemáticos. Diante dos resultados obtidos os canceladores de ruído adaptativos apresentaram melhores resultados com relação às outras técnicas de filtragem. Apesar de não ter sido adequada para a filtragem, a transformada wavelet mostrou-se uma poderosa ferramenta de análise de sinais, em virtude da sua característica multiresolução. A técnica utilizada para reconhecer os padrões do sinal mostrou bons resultados com os sinais analisados. / This work has the purpose to analyze some techniques for myoelectric signal processing, towards a subsequent implementation of a circuit which can recognize this signal and present as output a control signal to be used in rehabilitation systems. Simulation and evaluation of three filtering techniques for the myoelectric signal were done in order to attenuate the main interferences of noises which corrupt this signal. The evaluated techniques were: classic digital filtering; adaptive noise cancelling and the signal reconstruction through the obtained components by the wavelet transform. A simplified system of pattern recognition for this signal also was implemented and analyzed, accomplished through an artificial neural network. The myoelectric signal itself was applied to the input instead of its characteristics obtained by mathematical processing. According to the results obtained the adaptive noise cancelling presented better results in comparison to the other filtering techniques. Despite not being adequate for filtering, the wavelet transform proved to be a powerful tool for signal analysis, by virtue of its multiresolution characteristics. The technique used to recognize the signal patterns has shown good results with the analyzed signals.

Le déploiement des répéteurs iso-fréquence est une solution économique pour étendre la couverture d’un émetteur principal aux zones d’ombre. Cependant, ce mode de déploiement fait apparaître le phénomène des échos radio-fréquence entre antennes d’émission et de réception du répéteur. Selon les standards, un écho aussi faible soit-il réduit le débit de la liaison radio, tandis qu’un écho fort fait courir au répéteur le risque d’endommager ses circuits électroniques, ces risques sont dûs aux ondulations de puissance créées par les échos. L’objectif de cette thèse à caractère industriel est d’étudier ce phénomène naturel en considérant des signaux provenant de différents standards des télécommunications. Cette étude permet une caractérisation des échos radio-fréquence pour mieux s’orienter vers une solution optimisée et industriellement réalisable.Nous nous sommes orientés vers la solution du traitement du signal avancé en favorisant le filtrage adaptatif pour sa rapidité de convergence et sa simplicité relative d’implantation matérielle. Les circuits reconfigurables sont retenus pour leur prix et leur souplesse. L’implantation des solutions est effectuée en virgule fixe afin de satisfaire les exigences de réactivité. Durant la mise en oeuvre de la solution anti-écho, nous avons proposé une multitude de solutions numériques souples et fiables. À partir de ce constat, notre partenaire industriel a décidé de généraliser ce mode de traitement par le développement, la fabrication et la commercialisation de répéteurs de nouvelle génération entièrement numériques. / On-frequency repeaters are a cost-effective solution to extend coverage and enhance wireless communications, especially in shadow areas. However, coupling between the receiving antenna and the transmitting antenna, called radio frequency echo, increases modulation errors and creates oscillations in the system when the echo power is high. According to the communication standards, extremely weak echoes decrease the transmission rate, while strong echoes damage electroni ccircuits because of power peaks. This thesis aims at characterizing the echo phenomenon under different modulations, and proposing an optimized solution directly integrated to industry. We have turned to digital solutions especially the adaptive because of their high convergence rate and their simplicity to be implemented. The programmable circuits are chosen for their attractive price and their flexibility. When implementing echo cancellation solution, we proposed several reliable solutions, showing that digital processing is much more beneficial. For this reason, digital solutions are generalized, and the new generation of repeaters is fully digital.

Le nombre croissant d'appareils de diffusion de contenus audio pose le problème de partager le même espace physique sans partager lemême espace sonore. Les Sound Zones rendent possible la reproduction de programmes audio indépendants et spatialement séparés, àpartir d'un ensemble de haut-parleurs et de méthodes de reproduction de champs sonores. Le problème est alors décomposé en deuxzones : la Bright zone, où le contenu doit être reproduit et la Dark zone, où il doit être annulé. De nombreuses méthodes existent pourrésoudre ce problème, mais la plupart ne traite que le cas d'auditeurs en position statique. Elles s'appuient sur la résolution directe desméthodes d'optimisation adaptative, telle que la méthode de Pressure Matching (PM). Or, pour des utilisateurs en mouvement, cesméthodes ont un coût de calcul trop élevé, rendant impossible leur application à un problème dynamique. Le but de cette thèse est dedévelopper une solution présentant une complexité compatible avec un contrôle dynamique des Sound Zones, tout en conservant lesperformances des méthodes conventionnelles. Sous l'hypothèse que les déplacements sont lents, une résolution itérative du problème PMest proposée et évaluée. Les algorithmes LMS, NLMS et APA sont comparés sur la base de simulations en champ libre. La méthode LMSs'avère la plus avantageuse en termes de complexité, mais elle souffre d'une erreur de reproduction. Un effet mémoire limitant la réactivitédes algorithmes est aussi mis en évidence. Il est corrigé en implémentant une variante introduisant un facteur d'oubli (Variable LeakyLMS ou VLLMS). / The growing number of audio devices raises the problem of sharing the same physical space without sharing the same sound space. SoundZones make it possible to play independent and spatially separated audio programs by loudspeaker array in combination with sound fieldreproduction methods. The problem is then split into two zones: the Bright zone, where the audio content must be reproduced and theDark zone, where it must be cancelled. There are many methods available to solve this problem, but most only deal with auditors in astatic position. They are based on the direct resolution of adaptive optimization methods, such as the Pressure Matching (PM) method.However, for moving users, these methods have a too high computation cost, making it impossible to apply them to a dynamic problem.The aim of this thesis is to develop a solution offering a level of complexity compatible with a dynamic control of Sound Zones, whilemaintening the performance of conventional methods. Under the assumption that displacements are slow, an iterative resolution of the PMproblem is proposed and assessed. The LMS, NLMS and APA algorithms are compared on the basis of free field simulations. The LMSmethod is the most advantageous in terms of complexity, but it suffers from a reproduction error. A memory effect limiting the reactivityof the algorithms is also highlighted. It is corrected by implementing a leaky variant (Variable Leaky LMS or VLLMS) introducing aforgetting factor.

La problématique traitée dans cette thèse vise à développer une stratégie efficace de détection et de classification des impacts en présence d'incertitudes de modélisation du robot et de son environnement et en utilisant un nombre minimal de capteurs, notamment en l'absence de capteur d’effort.La première partie de la thèse porte sur la détection d'un impact pouvant avoir lieu à n'importe quel endroit du bras robotique et à n'importe quel moment de sa trajectoire. Les méthodes de détection d’impacts sont généralement basées sur un modèle dynamique du système, ce qui les rend sujettes au compromis entre sensibilité de détection et robustesse aux incertitudes de modélisation. A cet égard, une méthodologie quantitative a d'abord été mise au point pour rendre explicite la contribution des erreurs induites par les incertitudes de modèle. Cette méthodologie a été appliquée à différentes stratégies de détection, basées soit sur une estimation directe du couple extérieur, soit sur l'utilisation d'observateurs de perturbation, dans le cas d’une modélisation parfaitement rigide ou à articulations flexibles. Une comparaison du type et de la structure des erreurs qui en découlent et de leurs conséquences sur la détection d'impacts en a été déduite. Dans une deuxième étape, de nouvelles stratégies de détection d'impacts ont été conçues: les effets dynamiques des impacts sont isolés en déterminant la marge d'erreur maximale due aux incertitudes de modèle à l’aide d’une approche stochastique.Une fois l'impact détecté et afin de déclencher la réaction post-impact du robot la plus appropriée, la deuxième partie de la thèse aborde l'étape de classification. En particulier, la distinction entre un contact intentionnel (l'opérateur interagit intentionnellement avec le robot, par exemple pour reconfigurer la tâche) et un contact non-désiré (un sujet humain heurte accidentellement le robot), ainsi que la localisation du contact sur le robot, est étudiée en utilisant des techniques d'apprentissage supervisé et plus spécifiquement des réseaux de neurones feedforward. La généralisation à plusieurs sujet humains et à différentes trajectoires du robot a été étudiée. / The present thesis aims to develop an efficient strategy for impact detection and classification in the presence of modeling uncertainties of the robot and its environment and using a minimum number of sensors, in particular in the absence of force/torque sensor.The first part of the thesis deals with the detection of an impact that can occur at any location along the robot arm and at any moment during the robot trajectory. Impact detection methods are commonly based on a dynamic model of the system, making them subject to the trade-off between sensitivity of detection and robustness to modeling uncertainties. In this respect, a quantitative methodology has first been developed to make explicit the contribution of the errors induced by model uncertainties. This methodology has been applied to various detection strategies, based either on a direct estimate of the external torque or using disturbance observers, in the perfectly rigid case or in the elastic-joint case. A comparison of the type and structure of the errors involved and their consequences on the impact detection has been deduced. In a second step, novel impact detection strategies have been designed: the dynamic effects of the impacts are isolated by determining the maximal error range due to modeling uncertainties using a stochastic approach.Once the impact has been detected and in order to trigger the most appropriate post-impact robot reaction, the second part of the thesis focuses on the classification step. In particular, the distinction between an intentional contact (the human operator intentionally interacts with the robot, for example to reconfigure the task) and an undesired contact (a human subject accidentally runs into the robot), as well as the localization of the contact on the robot, is investigated using supervised learning techniques and more specifically feedforward neural networks. The challenge of generalizing to several human subjects and robot trajectories has been investigated.

It is known that a matched filter is optimal for a signal corrupted by Gaussian noise. In a wireless environment, the received signal may be corrupted by Gaussian noise and a variety of other channel disturbances: cochannel interference, multiple access interference, large and small-scale fading, etc. Adaptive filtering is the usual approach to mitigating this channel distortion. Existing adaptive filtering techniques usually attempt to minimize the mean square error (MSE) of some aspect of the received signal, with respect to the desired aspect of that signal. Adaptive minimization of MSE does not always guarantee minimization of bit error rate (BER). The main focus of this research involves estimation of the probability density function (PDF) of the received signal; this PDF estimate is used to adaptively determine a solution that minimizes BER. To this end, a new adaptive procedure called the Minimum BER Estimation (MBE) algorithm has been developed. MBE shows improvement over the Least Mean Squares (LMS) algorithm for most simulations involving interference and in some multipath situations. Furthermore, the new algorithm is more robust than LMS to changes in algorithm parameters such as stepsize and window width. / Master of Science

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[pt] Esta tese é composta de três artigos em que a ligação entre eles são modelos estatísticos com parametros variantes no tempo. Todos os artigos adotam um arcabouço que utiliza um mecanismo guiado pelos dados para a atualização dos parâmetros dos modelos. O primeiro explora a aplicação de uma nova classe de modelos de séries temporais não Gaussianas denominada modelos Generalized Autegressive Scores (GAS). Nessa classe de modelos, os parâmetros são atualizados utilizando o score da densidade preditiva. Motivamos o uso de modelos GAS simulando cenários conjuntos de fator de capacidade eólico. Nos últimos dois artigos, o gradiente descentente estocástico (SGD) é adotado para atualizar os parâmetros que variam no tempo. Tal metodologia utiliza a derivada de uma função custo especificada pelo usuário para guiar a otimização. A estrutura desenvolvida foi projetada para ser aplicada em um contexto de fluxo de dados contínuo, portanto, técnicas de filtragem adaptativa são exploradas para levar em consideração o concept-drift. Exploramos esse arcabouço com aplicações em segurança cibernética e infra-estrutura instrumentada. / [en] This thesis is composed of three papers in which the common ground among them is statistical models with time-varying parameters. All of them adopt a framework that uses a data-driven mechanism to update its coefficients. The first paper explores the application of a new class of non-Gaussian time series framework named Generalized Autoregressive Scores (GAS) models. In this class of models the parameters are updated using the score of the predictive density. We motivate the use of GAS models by simulating joint scenarios of wind power generation. In the last two papers, Stochastic Gradient Descent (SGD) is adopted to update time-varying parameters. This methodology uses the derivative of a user specified cost function to drive the optimization. The developed framework is designed to be applied in a streaming data context, therefore adaptive filtering techniques are explored to account for concept-drift.We explore this framework on cyber-security and instrumented infrastructure applications.

The great social and economic impact of earthquakes has made necessary the development of novel structural health monitoring (SHM) solutions for increasing the level of structural safety and assessment. SHM is the process of comparing the current state of a structure’s condition relative to a healthy baseline state to detect the existence, location, and degree of likely damage during or after a damaging input, such as an earthquake. Many SHM algorithms have been proposed in the literature. However, a large majority of these algorithms cannot be implemented in real time. Therefore, their results would not be available during or immediately after a major event for urgent post-event response and decision making. Further, these off-line techniques are not capable of providing the input information required for structural control systems for damage mitigation. The small number of real-time SHM (RT-SHM) methods proposed in the past, resolve these issues. However, these approaches have significant computational complexity and typically do not manage nonlinear cases directly associated with relevant damage metrics. Finally, many available SHM methods require full structural response measurement, including velocities and displacements, which are typically difficult to measure. All these issues make implementation of many existing SHM algorithms very difficult if not impossible. This thesis proposes simpler, more suitable algorithms utilising a nonlinear Bouc-Wen hysteretic baseline model for RT-SHM of a large class of nonlinear hysteretic structures. The RT-SHM algorithms are devised so that they can accommodate different levels of the availability of design data or measured structural responses, and therefore, are applicable to both existing and new structures. The second focus of the thesis is on developing a high-speed, high-resolution, seismic structural displacement measurement sensor to enable these methods and many other SHM approaches by using line-scan cameras as a low-cost and powerful means of measuring structural displacements at high sampling rates and high resolution. Overall, the results presented are thus significant steps towards developing smart, damage-free structures and providing more reliable information for post-event decision making.