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Dissertations / Theses on the topic 'Estimation'
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1
Yu, Kan Chi Kent. "Harmonic State Estimation and Transient State Estimation." Thesis, University of Canterbury. Electrical and Computer Engineering, 2006. http://hdl.handle.net/10092/1108.
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This thesis describes the algorithms and techniques developed for harmonic state estimation and transient state estimation, which can be used to identify the location of disturbance sources in an electrical power system. The previous harmonic state estimation algorithm is extended to include the estimation of time-varying harmonics using an adaptive Kalman filter. The proposed method utilises two covariance noise models to overcome the divergence problem in traditional Kalman filters. Moreover, it does not require an optimal covariance noise matrix of the Kalman filter to be used. The common problems faced in harmonic state estimation applications due to the influence of measurement bad data associated with measurements and the lack of measurement points, hence the system being partially observable, are investigated with reference to the Lower South Island of the New Zealand system. The state estimation technique is also extended to transient state estimation. Two formulation methods are outlined and the development of the proposed methodology is presented. Fault scenarios with reference to the Lower South Island of the New Zealand system are simulated to demonstrate the ability of transient state estimation in estimating the voltages and currents of the unmeasured locations, and applying the estimated results to search for the fault location. The estimation results are compared with PSCAD/EMTDC simulations to justify their accuracy.
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Telmoudi, Fedya. "Estimation and misspecification Risks in VaR estimation." Thesis, Lille 3, 2014. http://www.theses.fr/2014LIL30061/document.
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Dans cette thèse, nous étudions l'estimation de la valeur à risque conditionnelle (VaR) en tenant compte du risque d'estimation et du risque de modèle. Tout d'abord, nous considérons une méthode en deux étapes pour estimer la VaR. La première étape évalue le paramètre de volatilité en utilisant un estimateur quasi maximum de vraisemblance généralisé (gQMLE) fondé sur une densité instrumentale h. La seconde étape estime un quantile des innovations à partir du quantile empirique des résidus obtenus dans la première étape. Nous donnons des conditions sous lesquelles l'estimateur en deux étapes de la VaR est convergent et asymptotiquement normal. Nous comparons également les efficacités des estimateurs obtenus pour divers choix de la densité instrumentale h. Lorsque l'innovation n'est pas de densité h, la première étape donne généralement un estimateur biaisé de paramètre de volatilité et la seconde étape donne aussi un estimateur biaisé du quantile des innovations. Cependant, nous montrons que les deux erreurs se contrebalancent pour donner une estimation consistante de la VaR. Nous nous concentrons ensuite sur l'estimation de la VaR dans le cadre de modèles GARCH en utilisant le gQMLE fondé sur la classe des densités instrumentales double gamma généralisées qui contient la distribution gaussienne. Notre objectif est de comparer la performance du QMLE gaussien par rapport à celle du gQMLE. Le choix de l'estimateur optimal dépend essentiellement du paramètre d qui minimise la variance asymptotique. Nous testons si le paramètre d qui minimise la variance asymptotique est égal à 2. Lorsque le test est appliqué sur des séries réelles de rendements financiers, l'hypothèse stipulant l'optimalité du QMLE gaussien est généralement rejetée. Finalement, nous considérons les méthodes non-paramétriques d'apprentissage automatique pour estimer la VaR. Ces méthodes visent à s'affranchir du risque de modèle car elles ne reposent pas sur une forme spécifique de la volatilité. Nous utilisons la technique des machines à vecteurs de support pour la régression (SVR) basée sur la fonction de perte moindres carrés (en anglais LS). Pour améliorer la solution du modèle LS-SVR nous utilisons les modèles LS-SVR pondérés et LS-SVR de taille fixe. Des illustrations numériques mettent en évidence l'apport des modèles proposés pour estimer la VaR en tenant compte des risques de spécification et d'estimationIn this thesis, we study the problem of conditional Value at Risk (VaR) estimation taking into account estimation risk and model risk. First, we considered a two-step method for VaR estimation. The first step estimates the volatility parameter using a generalized quasi maximum likelihood estimator (gQMLE) based on an instrumental density h. The second step estimates a quantile of innovations from the empirical quantile of residuals obtained in the first step. We give conditions under which the two-step estimator of the VaR is consistent and asymptotically normal. We also compare the efficiencies of the estimators for various instrumental densities h. When the distribution of is not the density h the first step usually gives a biased estimator of the volatility parameter and the second step gives a biased estimator of the quantile of the innovations. However, we show that both errors counterbalance each other to give a consistent estimate of the VaR. We then focus on the VaR estimation within the framework of GARCH models using the gQMLE based on a class of instrumental densities called double generalized gamma which contains the Gaussian distribution. Our goal is to compare the performance of the Gaussian QMLE against the gQMLE. The choice of the optimal estimator depends on the value of d that minimizes the asymptotic variance. We test if this parameter is equal 2. When the test is applied to real series of financial returns, the hypothesis stating the optimality of Gaussian QMLE is generally rejected. Finally, we consider non-parametric machine learning models for VaR estimation. These methods are designed to eliminate model risk because they are not based on a specific form of volatility. We use the support vector machine model for regression (SVR) based on the least square loss function (LS). In order to improve the solution of LS-SVR model, we used the weighted LS-SVR and the fixed size LS-SVR models. Numerical illustrations highlight the contribution of the proposed models for VaR estimation taking into account the risk of specification and estimation
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Hoff, J. C. "Aircraft parameter estimation by estimation - before - modelling technique." Thesis, Cranfield University, 1995. http://dspace.lib.cranfield.ac.uk/handle/1826/10748.
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The use of the
estímation-before-modellíng (EBM) two step identification
procedure for the determination of aircraft aerodynamic derivatives from flight
test data is
analysed and illustrated. In the first step of the identification
procedure the usual Extended Kalman Filter (EKF) associated with the Modified
Bryson-Frazíer (MBF) smoother is compared with a new alterative filtering and
smoothing process. The new smoother is simpler and less computationally
demanding than the MBF smoother. However, its main advantage is that it
enables simultaneous data
smoothing with state derivative estimation, thereby
avoiding the need for a separate differentiation algorithm. The new smoother differentiator
has an
important feature that is the determination of the noise
characteristics of the measurement
signal under analysis prior to the smoothing
process. This is done by variance matching between the theoretical and
measured autocorrelation of the innovation
process generated by a Kalman filter.
The new
technique is compared with the old one by determining the aerodynamic
models for a EMB-312 Tucano dutch roll manoeuvre. It is demonstrated that
the new smoother
may be used to replace the MBF. Otherwise the new
technique
is used in the
analysis of the Handley Page Jetstream-100 aircraft low speed
controls free
phugoid trying to identify the contribution of the power Variation
observed
during the phugoid to the stability of the oscillation. Finally the models
obtained from the
phugoid analysis are reprocessed using the Total Least Square
regression and the results are compared with those from the ordinary Least
Square formulation.
4
Reynard, D. M. "Nonlinear estimation." Thesis, University of Newcastle Upon Tyne, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336142.
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Mu, Yingfei. "Boundary Estimation." Diss., North Dakota State University, 2015. http://hdl.handle.net/10365/25195.
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The existing statistical methods do not provide a satisfactory solution to determining the
spatial pattern in spatially referenced data, which is often required by research in many areas
including geology, agriculture, forestry, marine science and epidemiology for identifying the source
of the unusual environmental factors associated with a certain phenomenon. This work provides
a novel algorithm which can be used to delineate the boundary of an area of hot spots accurately
and e ciently. Our algorithm, rst of all, does not assume any pre-speci ed geometric shapes
for the change-curve. Secondly, the computation complexity by our novel algorithm for changecurve
detection is in the order of O(n2), which is much smaller than 2O(n2) required by the CUSP
algorithm proposed in M uller&Song [8] and Carlstein's [2] estimators. Furthermore, our novel
algorithm yields a consistent estimate of the change-curve as well as the underlying distribution
mean of observations in the regions. We also study the hypothesis test of the existence of the
change-curve in the presence of independence of the spatially referenced data. We then provide
some simulation studies as well as a real case study to compare our algorithm with the popular
boundary estimation method : Spatial scan statistic.
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Völcker, Björn. "Performance Analysis of Parametric Spectral Estimators." Doctoral thesis, KTH, Signals, Sensors and Systems, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3323.
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Baba, Harra M'hammed. "Estimation de densités spectrales d'ordre élevé." Rouen, 1996. http://www.theses.fr/1996ROUES023.
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Dans cette thèse nous construisons des estimateurs de la densité spectrale du cumulant, pour un processus strictement homogène et centré, l'espace des temps étant l'espace multidimensionnel, euclidien réel ou l'espace multidimensionnel des nombres p-adiques. Dans cette construction nous avons utilisé la méthode de lissage de la trajectoire et un déplacement dans le temps ou la méthode de fenêtres spectrales. Sous certaines conditions de régularité, les estimateurs proposés sont asymptotiquement sans biais et convergents. Les procédures d'estimation exposées peuvent trouver des applications dans de nombreux domaines scientifiques et peuvent aussi fournir des éléments de réponse aux questions relatives à certaines propriétés statistiques des processus aléatoires.
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Verma, Vishash. "Improved Slope Estimation in Organic Field-Effect Transistor Mobility Estimation." Kent State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=kent1618703169092189.
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Chauvin, Jonathan. "Estimation et contrôle d’un moteur HCCI. Estimation des systèmes périodiques." Paris, ENMP, 2006. http://www.theses.fr/2006ENMP1387.
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La combustion homogène Diesel (HCCI : Homogeneous Charge Compression Ignition) est caractérisée par un très fort taux de recirculation de gaz brûlés (EGR : Exhaust Gas Recirculation). Cette technique de combustion permet d’augmenter la qualité de mélange et la dilution dans le cylindre, tout en réduisant la formation des polluants. Malheureusement, ce procédé nuit à la stabilité de la combustion. Un compromis est nécessaire entre la stabilité de combustion et les performances du moteur, quantifiées en terme de couple produit, de bruit et d’émissions polluantes. C’est là le rôle du moteur. À fins d’implémentation de stratégie de contrôle, il est nécessaire d’estimer en temps réel l’évolution des paramètres de combustion qui ne sont pas directement mesurés par des capteurs. Cette thèse, réalisée en collaboration avec l’IFP (Institut Français du Pétrole), propose des algorithmes de contrôle qui ont été validés expérimentalement sur un moteur HCCI quatre cylindres développés par l’IFP. Nous décomposons le problème en trois parties et proposons des solutions, validées sur banc moteur, pour les deux premières. La première étape consiste à réaliser le contrôle de la boucle d’air. Le but est d’estimer et de contrôler les masses aspirées par des cylindres (air frais et gaz brûlés). Ces masses s’expriment directement en fonction de la pression, la composition et les débits du collecteur d’admission. Des observateurs non linéaires permettent d’estimer ces variables, en n’utilisant que les capteurs présents sur les véhicules de séries. La construction de ces observateurs ainsi que leurs preuves de convergence utilisent la méthode dite « d’injection de sortie » ainsi que la théorie de stabilité de Lyapunov. Une technique de génération de trajectoires est utilisée pour définir des consignes de débits (air frais et EGR). Cette loi de commande boucle ouverte prend explicitement en copte les contraintes physiques. Enfin, des contrôleurs de type promotionnel intégral (PI) sont utilisés pour garantir le suivi des consignes prescrites. Nous décrivons les résultats expérimentaux obtenus dans différents cas de figures, tels que des transitoires de charge et le cycle de référence européen. La deuxième étape est l’équilibrage cylindre à cylindre. Le but est d’estimer les paramètres de combustion de chacun des cylindres afin de garantir que les cylindres ont la même combustion en dépit de la variabilité des éléments techniques les constituant. Pour cela, nous créons un observateur de couple instantané et un observateur de richesse cylindre à cylindre à partir de capteurs présents sur les véhicules de séries. Nous exploitons l’information de haute fréquence contenue dans les signaux mesurés (échantillonnage aux 6 degrés vilebrequin). Ces observateurs sont validés expérimentalement. Leur conception est nouvelle. Il s’agit d’un nouveau type d’observateurs asymptotiques reconstituant un nombre arbitraire de fréquences d’un signal périodique inconnu entrant dans un système linéaire périodique. Ces observateurs surpassent (à performances comparables) les filtres de Kalman en terme de temps de calculs. Ils sont inspirés des techniques de moyennisation. Une méthodologie de réglage automatique est proposée et justifiée par l’extension à un nombre infini de fréquences. La troisième étape est le contrôle de la boucle de fuel. Durant des transitoires de couples, la boucle de carburant doit suivre la dynamique plus lente de la boucle d’air (qui est typiquement 10 fois plus lente). Nous décrivons cette problématique et expliquons les principales difficultésHomogeneous Charge Compression Ignition (HCCI) combustion is characterized by a very high rate of Exhaust Gas Recirculation (EGR). This improves mixing and dulution in the cylinders, reduces polluant formation at the expense of combustion stability. Thus HCCI engines requuires real-time control to ensure a good trade-off between performance (in terms of torque productio and low polluant emissions) and combustion stability. Such closed-loop control are based on estimation of combustion parameters that not directly measured. This thesis, supported by IFP (Institut Français du Péttrole), proposes some control algorithms that have been tested experimentaly on a 4 cylinders HCCI engine developed by IFP. We decompose the control synthesis in three steps. We propose solutions with experimental validations for the first two steps. The first steps is air path control. The goal is to estimate and to control the masses entering in the cylinders (fresh air and burned gas). These masses are directly related to collecctor pressure, compositions and flow-rates. These variables are estimated via nonlinear observers using commercial cars sensors. Design and theoretical convergence proof follow linearization via output injection and Lyapunov argument. Feedforward control based on motion planning for differentially flat systems are used to derive the flow-rate set points (fresh air and EGR). This feedfoward control takes explicitly physical input constraints into account. Finally, fast Proportional Integral (PI) controller are designed to track these step points unsing as measured values the aboves estimations. We describe experimental results for large torque transient and also driving phases of the eurocycle. The second step is cylinders balancing. The goal is to estimate and control the combustion parameters in order to guarantee that all the cylinders have the same combustion in any steady-state regime . For that, we designedinstantaneous torque and cylinder individual air/fuel ratio (AFR) observers using commercial car sensors. We exploit here the highfrequency information contained in the measured signals (sampling of 6 degree crank angle). Experimenal results are reported. These results are based on a new class on asymptotic observers of an arbitrary numbers of Fournier modes associated to an unknown periodic input entering a linear time-periodic system. These observers outperform Kalman filters in terms of computation burden. Design and convergence proof are based on averaging techniques. A gain design methodology is proposed and justified for large numbers of modes via extension to infinite dimension of the finite-dimensional convergence analysis. The third step is the fuel path control. During large transient, the fuel path must follow the slower air path transient. We describe this still open problematic and point out its main difficulties
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Srinivasarengan, Krishnan. "Estimation d'état, estimation paramétrique et identifiabilité des modèles quasi-LPV." Thesis, Université de Lorraine, 2018. http://www.theses.fr/2018LORR0059/document.
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Dans cette thèse, deux problèmes liés aux approches basées sur des modèles pour le diagnostic de défauts et l'estimation du niveau de dégradation des équipements dans un bâtiment sont étudiés: la conception d'observateurs adaptatifs pour l'estimation de l'état et des paramètres, et l'analyse de l'identifiabilité des paramètres. La classe des modèles considérés est celle des modèles quasi-linéaires à paramètres variants dans le temps (quasi-LPV) avec paramétrisation affine des matrices d'état. Utilisant l'approche polytopique de Takagi-Sugeno (T-S), deux types d'observateurs sont proposés, un pour des systèmes en temps continu et l'autre pour des systèmes en temps discret. La structure de Luenberger (correction de la dynamique à l'aide de l'erreur d'estimation de la sortie) est choisie pour la partie d'estimation d'état de l'observateur pour les deux et leur conception s'appuie sur l'approche de Lyapunov. Pour la partie d'estimation des paramètres, une structure originale est proposée en temps continu et une structure proportionnelle-intégrale (PI) est utilisée en temps discret. La troisième contribution présente succinctement une méthode d'estimation d'état et des paramètres de façon découplée. Elle utilise conjointement l'approche de l'espace de parité et un observateur à mémoire finie. Pour la quatrième contribution relative à l'identifiabilité des paramètres, les états du système sont tout d'abord éliminés en utilisant une approche de type espace de parité. Cela permet d'extraire le `résumé exhaustif' du modèle qui aide à établir l'identifiabilité du modèle. Tous les résultats sont illustrés à l'aide d'exemplesTwo problems relevant to the model-based approaches to fault diagnosis and degradation estimation in commissioned buildings are investigated in this thesis: adaptive observers for state and parameter estimation, and parameter identifiability. The system models considered are the quasi-LPV models with affine parameterization. Using the Takagi-Sugeno (T-S) polytopic approach, two observer designs, one for continuous-time models and another for discrete-time models are provided. Both models use a Luenberger structure for the state estimation part and deploy the Lyapunov design approach. An innovative non-linear estimation model is obtained through the design process for the continuous-time parameter estimation whereas a proportional-integral (PI) structure is used for discrete-time. A brief third contribution is a decoupled state and parameter estimation that makes use of the parity-space approach and realized using a finite memory observer strategy. For the fourth contribution of parameter identifiability, a parity-space formulation using null-space computation is used for the elimination of states of the model from which the exhaustive summary of the model is extracted and the identifiability of the model verified. All the results are illustrated using examples
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Srinivasarengan, Krishnan. "Estimation d'état, estimation paramétrique et identifiabilité des modèles quasi-LPV." Electronic Thesis or Diss., Université de Lorraine, 2018. http://www.theses.fr/2018LORR0059.
Full textAbstract:
Dans cette thèse, deux problèmes liés aux approches basées sur des modèles pour le diagnostic de défauts et l'estimation du niveau de dégradation des équipements dans un bâtiment sont étudiés: la conception d'observateurs adaptatifs pour l'estimation de l'état et des paramètres, et l'analyse de l'identifiabilité des paramètres. La classe des modèles considérés est celle des modèles quasi-linéaires à paramètres variants dans le temps (quasi-LPV) avec paramétrisation affine des matrices d'état. Utilisant l'approche polytopique de Takagi-Sugeno (T-S), deux types d'observateurs sont proposés, un pour des systèmes en temps continu et l'autre pour des systèmes en temps discret. La structure de Luenberger (correction de la dynamique à l'aide de l'erreur d'estimation de la sortie) est choisie pour la partie d'estimation d'état de l'observateur pour les deux et leur conception s'appuie sur l'approche de Lyapunov. Pour la partie d'estimation des paramètres, une structure originale est proposée en temps continu et une structure proportionnelle-intégrale (PI) est utilisée en temps discret. La troisième contribution présente succinctement une méthode d'estimation d'état et des paramètres de façon découplée. Elle utilise conjointement l'approche de l'espace de parité et un observateur à mémoire finie. Pour la quatrième contribution relative à l'identifiabilité des paramètres, les états du système sont tout d'abord éliminés en utilisant une approche de type espace de parité. Cela permet d'extraire le `résumé exhaustif' du modèle qui aide à établir l'identifiabilité du modèle. Tous les résultats sont illustrés à l'aide d'exemplesTwo problems relevant to the model-based approaches to fault diagnosis and degradation estimation in commissioned buildings are investigated in this thesis: adaptive observers for state and parameter estimation, and parameter identifiability. The system models considered are the quasi-LPV models with affine parameterization. Using the Takagi-Sugeno (T-S) polytopic approach, two observer designs, one for continuous-time models and another for discrete-time models are provided. Both models use a Luenberger structure for the state estimation part and deploy the Lyapunov design approach. An innovative non-linear estimation model is obtained through the design process for the continuous-time parameter estimation whereas a proportional-integral (PI) structure is used for discrete-time. A brief third contribution is a decoupled state and parameter estimation that makes use of the parity-space approach and realized using a finite memory observer strategy. For the fourth contribution of parameter identifiability, a parity-space formulation using null-space computation is used for the elimination of states of the model from which the exhaustive summary of the model is extracted and the identifiability of the model verified. All the results are illustrated using examples
12
Larsson, Martin. "Road Slope Estimation." Thesis, Linköping University, Automatic Control, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-53884.
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Knowledge about the current road slope can improve several applications in a heavy-duty vehicle such as predictive cruise control and automated gearbox control. In this thesis the possibility of estimating the road slope based on signals from a vehicles air suspension system has been studied. More specifically, the measurement consists of a pressure signal measuring the axle load, and a vertical distance sensor.
A variety of suspension systems can be mounted on a Scania truck. During this thesis, two discrete-time models based on two different rear axle air suspension systems have been proposed. The models use the effect of alternating axle load during a change in the road slope and the estimates are computed using an extended Kalman filter.
The first model is based on a rear axle suspension known as the 2-bellow system. This type of suspension is strongly affected by the driveshaft torque, which results in a behaviour where the rear end is pushed upwards and thus decreasing the rear axle load during uphill driving. A model was developed in order to compensate for this behaviour. Unfortunately, the estimates showed less promising results and all attempts to determine the error was unsuccessful.
The latter model is based on the 4-bellow system. This suspension system is not affected by the driveshaft torque and a less complex model could be derived. The experimental results indicated that road slope estimation was possible and with a fairly accurate result. However, more work is needed since the estimate is affected by road surface irregularities and since the algorithm requires knowledge about the vehicles mass and the location of the centre of gravity.
All the presented results have been estimated based on real data from a test track at Scania Technical Centre in Södertälje.
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Li, Jiexiang. "Nonparametric spatial estimation." [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3223036.
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Thesis (Ph.D.)--Indiana University, Dept. of Mathematics, 2006."Title from dissertation home page (viewed June 28, 2007)." Source: Dissertation Abstracts International, Volume: 67-06, Section: B, page: 3167. Adviser: Lanh Tat Tran.
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Rosenhahn, Bodo. "Pose estimation revisited." Kiel Inst. für Informatik und Praktische Mathematik, 2003. http://e-diss.uni-kiel.de/diss_842/d842.pdf.
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Koski, Antti E. "Rapid frequency estimation." Worcester, Mass. : Worcester Polytechnic Institute, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-032806-165036/.
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Thesis (M.S.)--Worcester Polytechnic Institute.Keywords: DSS; ECM; SVD; Singular Value Decomposition; rapid frequency estimation; frequency estimation. Includes bibliographical references (leaves 174-177).
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Sart, Mathieu. "Estimation par tests." Phd thesis, Université Nice Sophia Antipolis, 2013. http://tel.archives-ouvertes.fr/tel-00931868.
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Cette thèse porte sur l'estimation de fonctions à l'aide de tests dans trois cadres statistiques différents. Nous commençons par étudier le problème de l'estimation des intensités de processus de Poisson avec covariables. Nous démontrons un théorème général de sélection de modèles et en déduisons des bornes de risque non-asymptotiques sous des hypothèses variées sur la fonction à estimer. Nous estimons ensuite la densité de transition d'une chaîne de Markov homogène et proposons pour cela deux procédures. La première, basée sur la sélection d'estimateurs constants par morceaux, permet d'établir une inégalité de type oracle sous des hypothèses minimales sur la chaîne de Markov. Nous en déduisons des vitesses de convergence uniformes sur des boules d'espaces de Besov inhomogènes et montrons que l'estimateur est adaptatif par rapport à la régularité de la densité de transition. La performance de l'estimateur est aussi évalué en pratique grâce à des simulations numériques. La seconde procédure peut difficilement être implémenté en pratique mais permet d'obtenir un résultat général de sélection de modèles et d'en déduire des vitesses de convergence sous des hypothèses plus générales sur la densité de transition. Finalement, nous proposons un nouvel estimateur paramétrique d'une densité. Son risque est contrôlé sous des hypothèses pour lesquelles la méthode du maximum de vraisemblance peut ne pas fonctionner. Les simulations montrent que ces deux estimateurs sont très proches lorsque le modèle est vrai et suffisamment régulier. Il est cependant robuste, contrairement à l'estimateur du maximum de vraisemblance.
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Garcia, Jose F. "Ship's attitude estimation." Thesis, Monterey, California. Naval Postgraduate School, 1989. http://hdl.handle.net/10945/27261.
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Landing aircraft on board is a most delicate phase of flight operations at sea. The ability to predict the aircraft carrier's motion over an interval of several seconds within reasonable error bounds may allow improvement in touchdown dispersion and a more certain value for a ramp clearance due to a smoother aircraft trajectory. Also, improved information to the Landing Signal Officer should decrease the number of waveoffs. This work indicates and shows graphically that, based on the data for pitch, heave and roll measured for various ships and sea conditions, the motion can be predicted well. The predictor was designed on the basis of Kalman's optimum filtering theory for the discrete time case, adapted for real-time digital computer operation
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Nasir, Imtiaz Hussain. "Multivariable inferential estimation." Thesis, University of Newcastle Upon Tyne, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.273370.
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Kibua, Titus Kithanze. "Variance function estimation." Thesis, City University London, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282078.
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Schneider, Michael K. (Michael Klaus). "Krylov subspace estimation." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8983.
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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.Includes bibliographical references (p. 151-156).
This thesis proposes a new iterative algorithm for the simultaneous computation of linear least-squares estimates and error variances. There exist many iterative methods for computing only estimates. However, most of these will not also compute error variances. A popular method for computing only estimates is the conjugate gradient algorithm. The algorithm proposed in this thesis for the simultaneous computation of estimates and error variances is a variant of the conjugate gradient algorithm for computing estimates. The convergence of the proposed algorithm is extensively characterized both analytically and experimentally. Variants of the proposed estimation algorithm are applied to two other statistical problems. The first is that of realization. Specifically, an iterative algorithm is developed for the simultaneous generation of a sample path of a given Gaussian random process and a low-rank approximation to the covariance matrix of a given process. The algorithm is compared to existing algorithms for realization in terms of an analytical estimate of computational cost and an experimental characterization of overall performance. The second statistical problem is that of space-time estimation. This thesis proposes an implementation of the Kalman filter and smoother in which each step of these recursive algorithms is solved iteratively. The resulting space-time estimation algorithm is especially suited for remote sensing problems. In particular, the algorithm is applied to the assimilation of measurements of sea surface height into a model of the ocean, the dynamics of which are given by a Rossby wave equation. Lastly, this thesis examines the stability of infinite-dimensional discrete-time Kalman filters of a type arising in remote sensing problems. This is accomplished by developing a Lyapunov theory for infinite-dimensional linear systems whose states are elements in a Hilbert space. Two theorems, proved in this thesis, provide sufficient conditions for the state trajectories to converge either strongly or weakly to 0. This general theory is then used to establish sufficient conditions for strong and weak stability of infinite-dimensional Kalman filters.
by Michael K. Schneider.
Ph.D.
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Alshammery, Hafiz Jaman 1971. "Interval attenuation estimation." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9877.
Full textAbstract:
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 1998.Includes bibliographical references (leaves 55-56).
by Hafiz Jaman Alshammery.
S.M.
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Hui, Kin-Ping. "Network reliability estimation." Title page, table of contents and abstract only, 2005. http://hdl.handle.net/2440/37952.
Full textAbstract:
Computing the reliability of a network is a #P-complete problem, therefore estimation by means of simulation often becomes a favourable choice. In modern communication networks, link failure probabilities are usually small and hence network failures become rare events. This poses a challenge to estimate the network reliability. In this thesis we present different techniques for network reliability estimation. There are two main sampling techniques in reliability estimation: combinatorial and permutational sampling. Combinatorial sampling has the advantage of speed but has poor performance in rare event simulations. Permutational sampling gives good simulation performance but at a higher computational cost. We combine the two techniques and propose a hybrid sampling scheme called Tree Cut and Merge. By employing simple bounding together with clever conditional sampling, the TCM scheme achieves over 10(superscript 7) times speed up in certain classes of heterogeneous networks. The Crude Monte Carlo (combinatorial) component in the Tree Cut and Merge scheme may cause problems in some situations. In bad cases, the slow convergence problem re-appears. To address the problem, we modifed the scheme by introducing the Importance Sampling technique. The new Tree Cut and Merge with Importance Sampling scheme maintained the speed advantage of the Tree Cut and Merge and minimizes, at the same time, the potential problems caused by the Crude Monte Carlo component. Associated with the Importance Sampling technique, a new technique called the Cross-Entropy method has been developed in the late 90's to find the optimal Importance Sampling parameters. By employing the Cross-Entropy technique, we propose a new scheme called the Merge Process with Cross-Entropy. The new scheme improves the Merge Process in nearly all classes of network; in contrast, Tree Cut and Merge with Importance Sampling scheme sees the greatest improvement in heterogeneous networks. Besides estimating the reliability of a single network, this thesis also investigates a closely related problem: estimating the difference in reliability of two very similar networks. The problem is closely linked to the applications in the areas of network optimization, network evolution, reconfiguration and recovery, for example. The fact that the probabilities of rare events are hard to estimate makes estimating their difference even more difficult. Coupled and differential sampling techniques are proposed and applied to various schemes in this thesis. They prove to be superior to the conventional independent "estimate and subtract" method. Interestingly, these concepts also lead to new ideas regarding the estimation of the reliability of networks that are similar to networks with polynomially computable reliability.Thesis (Ph.D.)--School of Mathematical Sciences, 2005.
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Wong, Valerie (Valerie Wan Chi). "Feasibility of using cloud top altimetry for estimating tropical cyclone intensity estimation." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/114135.
Full textAbstract:
Thesis: S.B., Massachusetts Institute of Technology, Department of Earth, Atmospheric, and Planetary Sciences, 2006.Cataloged from PDF version of thesis. Some pages in the original thesis contain text that runs off the edge of the page.
Includes bibliographical references (pages 36-37).
This project explores whether cloud top altimetry can be used as an accurate and reliable means of estimating the intensity of tropical cyclones. Professor Kerry A. Emanuel developed the theory that is under investigation. His theory aims to calculate the peak surface wind speed in hurricanes using only three parameters, all of which can be collected from satellite imagery: cloud top height, sea surface temperature and cloud top temperature. Cloud top heights for selected hurricanes were obtained from the ICESat, and points were identified where the ICESat may have traversed the hurricanes. These points were compared with IR images to confirm the intersection of the ICESat track and the hurricane tracks. Out of 18 hurricanes examined, four provided feasible points to test this new technique. Two of these points were from hurricanes that were at the end stage of their life cycle; these two data points were discarded. Data from the two usable data points were compared to the recorded wind speeds from Unisys. It seems that the new method is overestimating the maximum surface wind speed by less than 10%. Two data points are insufficient for conclusively validating this technique. However, this project has established a viable method for gathering and analyzing altimetry data, providing a basis for further testing of the theory.
by Valerie Wong.
S.B.
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Navarro, Myra C. "Small area estimation : estimating selected economic statistics for provinces of the Philippines." Thesis, Canberra, ACT : The Australian National University, 1992. http://hdl.handle.net/1885/116918.
Full textAbstract:
Different methods of small area estimation are discussed in detail together with a summary of the
applications for each method. A case study consisting of an application to small area estimation of
selected Philippine economic data (employment, salary and value of output) are described. Seven
different estimators are applied to this problem of estimating intercensal small area
characteristics; 3 synthetic estimators, a SPREE estimator, a RATIO-SPREE estimator and 2
regression-based estimators. In addition, estimates of the variance of each estimator are derived.
The various estimators are evaluated on the basis of their performance in replicating the 1988
Census of Establishments (CE) preliminary estimates. The absolute relative error percentage and the
root mean square error are used in assessing the performance of each estimator. The SPREE is a best
choice based on percentage absolute relative error while the RATIO-SPREE estimator is the most
accurate in terms of root mean square error.
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Chauvin, Jonathan. "Estimation et contrôle d'un moteur diesel HCCI. Estimation des systèmes périodiques." Phd thesis, École Nationale Supérieure des Mines de Paris, 2006. http://pastel.archives-ouvertes.fr/pastel-00002804.
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Mase, Takahiko, Yasushi Hirano, Shoji Kajita, and Kenji Mase. "Improving Accuracy of WLAN-Based Location Estimation by Using Recursive Estimation." IEEE, 2007. http://hdl.handle.net/2237/9518.
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Tewfik, Ahmed H. "Recursive estimation and spectral estimation for 2-D isotropic random fields." Thesis, Massachusetts Institute of Technology, 1987. http://hdl.handle.net/1721.1/14928.
Full textAbstract:
Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1987.MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING
Bibliography: leaves 180-188.
by Ahmed Hossam Tewfik.
Sc.D.
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Onnen, Nathaniel J. "Estimation of Bivariate Spatial Data." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1616243660473062.
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Zheng, Xueying, and 郑雪莹. "Robust joint mean-covariance model selection and time-varying correlation structure estimation for dependent data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hub.hku.hk/bib/B50899703.
Full textAbstract:
In longitudinal and spatio-temporal data analysis, repeated measurements from a subject can be either regional- or temporal-dependent. The correct specification of the within-subject covariance matrix cultivates an efficient estimation for mean regression coefficients.
In this thesis, robust estimation for the mean and covariance jointly for the regression model of longitudinal data within the framework of generalized estimating equations (GEE) is developed. The proposed approach integrates the robust method and joint mean-covariance regression modeling. Robust generalized estimating equations using bounded scores and leverage-based weights are employed for the mean and covariance to achieve robustness against outliers. The resulting estimators are shown to be consistent and asymptotically normally distributed.
Robust variable selection method in a joint mean and covariance model is considered, by proposing a set of penalized robust generalized estimating equations to estimate simultaneously the mean regression coefficients, the generalized autoregressive coefficients and innovation variances introduced by the modified Cholesky decomposition. The set of estimating equations select important covariate variables in both mean and covariance models together with the estimating procedure. Under some regularity conditions, the oracle property of the proposed robust variable selection method is developed. For these two robust joint mean and covariance models, simulation studies and a hormone data set analysis are carried out to assess and illustrate the small sample performance, which show that the proposed methods perform favorably by combining the robustifying and penalized estimating techniques together in the joint mean and covariance model.
Capturing dynamic change of time-varying correlation structure is both interesting and scientifically important in spatio-temporal data analysis. The time-varying empirical estimator of the spatial correlation matrix is approximated by groups of selected basis matrices which represent substructures of the correlation matrix. After projecting the correlation structure matrix onto the space spanned by basis matrices, varying-coefficient model selection and estimation for signals associated with relevant basis matrices are incorporated. The unique feature of the proposed model and estimation is that time-dependent local region signals can be detected by the proposed penalized objective function. In theory, model selection consistency on detecting local signals is provided. The proposed method is illustrated through simulation studies and a functional magnetic resonance imaging (fMRI) data set from an attention deficit hyperactivity disorder (ADHD) study.published_or_final_version
Statistics and Actuarial Science
Doctoral
Doctor of Philosophy
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Läuter, Henning. "Estimation in partly parametric additive Cox models." Universität Potsdam, 2003. http://opus.kobv.de/ubp/volltexte/2011/5150/.
Full textAbstract:
The dependence between survival times and covariates is described e.g. by proportional hazard models. We consider partly parametric Cox models and discuss here the estimation of interesting parameters. We represent the ma- ximum likelihood approach and extend the results of Huang (1999) from linear to nonlinear parameters. Then we investigate the least squares esti- mation and formulate conditions for the a.s. boundedness and consistency of these estimators.
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Agarwal, Arpit. "Statistical field estimation and scale estimation for complex coastal regions and archipelagos." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/49877.
Full textAbstract:
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 153-158).
A fundamental requirement in realistic computational geophysical fluid dynamics is the optimal estimation of gridded fields and of spatial-temporal scales directly from the spatially irregular and multivariate data sets that are collected by varied instruments and sampling schemes. In this work, we derive and utilize new schemes for the mapping and dynamical inference of ocean fields in complex multiply-connected domains, study the computational properties of our new mapping schemes, and derive and investigate new schemes for adaptive estimation of spatial and temporal scales. Objective Analysis (OA) is the statistical estimation of fields using the Bayesian-based Gauss-Markov theorem, i.e. the update step of the Kalman Filter. The existing multi-scale OA approach of the Multidisciplinary Simulation, Estimation and Assimilation System consists of the successive utilization of Kalman update steps, one for each scale and for each correlation across scales. In the present work, the approach is extended to field mapping in complex, multiply-connected, coastal regions and archipelagos. A reasonably accurate correlation function often requires an estimate of the distance between data and model points, without going across complex land-forms. New methods for OA based on estimating the length of optimal shortest sea paths using the Level Set Method (LSM) and Fast Marching Method (FMM) are derived, implemented and utilized in general idealized and realistic ocean cases.
(cont.) Our new methodologies could improve widely-used gridded databases such as the climatological gridded fields of the World Ocean Atlas (WOA) since these oceanic maps were computed without accounting for coastline constraints. A new FMM-based methodology for the estimation of absolute velocity under geostrophic balance in complicated domains is also outlined. Our new schemes are compared with other approaches, including the use of stochastically forced differential equations (SDE). We find that our FMM-based scheme for complex, multiply-connected, coastal regions is more efficient and accurate than the SDE approach. We also show that the field maps obtained using our FMM-based scheme do not require postprocessing (smoothing) of fields. The computational properties of the new mapping schemes are studied in detail. We find that higher-order schemes improve the accuracy of distance estimates. We also show that the covariance matrices we estimate are not necessarily positive definite because the Weiner Khinchin and Bochner relationships for positive deniteness are only valid for convex simply-connected domains. Several approaches to overcome this issue are discussed and qualitatively evaluated. The solutions we propose include introducing a small process noise or reducing the covariance matrix based on the dominant singular value decomposition.
(cont.) We have also developed and utilized novel methodologies for the adaptive estimation of spatial-temporal scales from irregularly spaced ocean data. The three novel methodologies are based on the use of structure functions, short term Fourier transform and second generation wavelets. To our knowledge, this is the first time that adaptive methodologies for the spatial-temporal scale estimation are proposed. The ultimate goal of all these methods would be to create maps of spatial and temporal scales that evolve as new ocean data are fed to the scheme. This would potentially be a significant advance to the ocean community for better understanding and sampling of ocean processes.
by Arpit Agarwal.
S.M.
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Qian, Li. "Web-based cost estimation and supplier selection based on parametric cost estimation /." Search for this dissertation online, 2003. http://wwwlib.umi.com/cr/ksu/main.
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Warner, Carl Michael 1952. "ESTIMATION OF NONSTATIONARY SIGNALS IN NOISE (PROCESSING, ADAPTIVE, WIENER FILTERS, ESTIMATION, DIGITAL)." Thesis, The University of Arizona, 1986. http://hdl.handle.net/10150/291297.
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Patriksson, Alfred. "Radio signal DOA estimation : Implementing radar signal direction estimation on an FPGA." Thesis, Linköpings universitet, Datorteknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-157144.
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This master’s thesis covers the design and implementation of a monopulse directionof arrival (DOA) estimation algorithm on an FPGA. The goal is to implement a complete system that is capable of estimating the bearing of an incident signal. In order to determine the estimate quality both a theoretical and practical noise analysis of the signal chain is performed. Special focus is placed on the statistical properties of the transformation from I/Q-demodulated signals with correlated noise to a polar representation. The pros and cons for three different methods of calculating received signal phasors are also covered.The system is limited to two receiving channels which constrains this report to a 2D analysis. In addition the used hardware is limited to C-band signals. We show that an FPGA implementation of monopulse techniques is definitely viable and that an SNR higher than ten dB allows for a gaussian approximation of the polar representationof an I/Q signal.
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Prohorenko, Didrik. "A forecasting approach to estimating cartel damages : The importance of considering estimation uncertainty." Thesis, Södertörns högskola, Nationalekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:sh:diva-41021.
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In this study, I consider the performance of simple forecast models frequently applied in counterfactual analysis when the information at hand is limited. Furthermore, I discuss the robustness of the standard t-test commonly used to statistically detect cartels. I empirically verify that the standard t-statistics encompasses parameter estimation uncertainty when one of the time series in a two-sided t-test has been estimated. Thereafter, I compare the results with those from a corrected t-test, recently proposed, where the uncertainty has been accounted for. The results from the study show that a simple OLS-model can be used to detect a cartel and to compute a counterfactual price when data is limited, at least as long as the price overcharge inflicted by the cartel members is relatively large. Yet, the level of accuracy may vary and at a point where the data used for estimating the model become relatively limited, the model predictions tend to be inaccurate.
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Carlsson, Martin. "Variance Estimation of the Calibration Estimator with Measurement Errors in the Auxiliary Information." Thesis, Örebro universitet, Handelshögskolan vid Örebro Universitet, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:oru:diva-68928.
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Geurtz, Alexander. "Model based shape estimation /." Lausanne : EPFL, 1993. http://library.epfl.ch/theses/?nr=1180.
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Kane, Roma. "Multiuser TDMA channel estimation." Diss., Columbia, Mo. : University of Missouri-Columbia, 2004. http://hdl.handle.net/10355/5810.
Full textAbstract:
Thesis (M.S.)--University of Missouri-Columbia, 2004.The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (June 30, 2006) Vita. Includes bibliographical references.
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Dituri, Joseph. "Ballistic missile trajectory estimation." Thesis, Monterey, Calif. : Naval Postgraduate School, 2006. http://bosun.nps.edu/uhtbin/hyperion.exe/06Dec%5FDituri.pdf.
Full textAbstract:
Thesis (M.S. in Astronautical Engineering)--Naval Postgraduate School, December 2006.Thesis Advisor(s): Kyle T. Alfriend, Don A. Danielson. "December 2006." Includes bibliographical references (p. 57). Also available in print.
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Nilsson, Martin. "Estimation of Radial Runout." Thesis, Linköping University, Department of Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8744.
Full textAbstract:
The demands for ride comfort quality in today's long haulage trucks are constantly growing. A part of the ride comfort problems are represented by internal vibrations caused by rotating mechanical parts. This thesis work focus on the vibrations generated from radial runout on the wheels. These long haulage trucks travel long distances on smooth highways, with a constant speed of 90 km/h resulting in a 7 Hz oscillation. This frequency creates vibrations in the cab, which can be found annoying. To help out with the vibration diagnosis when a truck enters a mechanical workshop, this work studies methods for radial runout detection using the wheel speed sensors.
The main idea is to represent the varying radius signal with a sinusoid, where the calculations are based on Fourier series. The estimated radial runout value is then the amplitude of the sinusoid. In addition to the detection part, the work also present results regarding how the relative phase difference between two wheels with radial runout effects the lateral motion of the cab.
This thesis work was performed at Scania CV AB in Södertälje, Sweden and all measurements have been full scale experiments on real trucks.
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Servien, Rémi. "Estimation de régularité locale." Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2010. http://tel.archives-ouvertes.fr/tel-00730491.
Full textAbstract:
L'objectif de cette thèse est d'étudier le comportement local d'une mesure de probabilité, notamment au travers d'un indice de régularité locale. Dans la première partie, nous établissons la normalité asymptotique de l'estimateur des kn plus proches voisins de la densité et de l'histogramme. Dans la deuxième, nous définissons un estimateur du mode sous des hypothèses affaiblies. Nous montrons que l'indice de régularité intervient dans ces deux problèmes. Enfin, nous construisons dans une troisième partie différents estimateurs pour l'indice de régularité à partir d'estimateurs de la fonction de répartition, dont nous réalisons une revue bibliographique.
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Thiam, Baba. "Estimation récursive de fonctionnelles." Phd thesis, Université de Versailles-Saint Quentin en Yvelines, 2006. http://tel.archives-ouvertes.fr/tel-00131199.
Full textAbstract:
L'objet de cette thèse est l'étude du comportement asymptotique d'estimateurs à noyau d'une densité de probabilité et de ses dérivées, d'une fonction de régression, ainsi que du mode et de la valeur modale d'une densité de probabilité. Le but est d'établir certaines propriétés des estimateurs à noyau récursifs ou semi-récursifs afin de comparer leur comportement asymptotique à celui des estimateurs classiques. Dans le premier chapitre, nous établissons des principes de grandes déviations (PGD) et des principes de déviations modérées (PDM) pour l'estimateur récursif d'une densité de probabilité et pour ses dérivées. Il s'avére que, dans les principes de déviations vérifiés par les estimateurs des dérivées, la fonction de taux est toujours une fonction quadratique, que les déviations soient grandes ou modérées. Contrairement, pour l'estimateur de la densité, les fonctions de taux qui apparaissent sont de nature différente selon que les déviations sont grandes ou modéerées. Les fonctions de taux qui apparaissent tant dans les PGD pour les dérivées que dans les PDM pour la densité et pour les dérivées sont plus grandes dans le cas où l'estimateur récursif est utilisé. Dans le deuxième chapitre, nous établissons des PGD et des PDM pour des estimateurs à noyau d'une fonction de régression. Nous généralisons les résultats déjà obtenus dans le cas unidimensionnel pour l'estimateur de Nadaraya-Watson. Nous étudions ensuite le comportement en déviations de la version semi-récursive de cet estimateur en établissant des PGD et des PDM. Les fonctions de taux qui apparaissent dans les PDM sont plus grandes pour l'estimateur semi-récursif que pour l'estimateur classique. Dans le troisième chapitre, nous nous intéressons à l'estimation jointe du mode et de la valeur modale d'une densité de probabilité basée sur l'estimateur à noyau récursif de la densité. Nous étudions la vitesse de convergence en loi et presque sûre du couple formé par ces deux estimateurs. Pour estimer simultanément les deux paramètres de façon optimale, il faut utiliser des fenêtres différentes pour définir chacun des deux estimateurs. Les estimateurs semi-récursifs conduisent à des variances asymptotiques plus petites que les estimateurs classiques.
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Rivoirard, Vincent. "Estimation bayésienne non paramétrique." Phd thesis, Université Paris-Diderot - Paris VII, 2002. http://tel.archives-ouvertes.fr/tel-00002149.
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Dans le cadre d'une analyse par ondelettes, nous nous intéressons à l'étude statistique d'une classe particulière d'espaces de Lorentz : les espaces de Besov faibles qui apparaissent naturellement dans le contexte de la théorie maxiset. Avec des hypothèses de type "bruit blanc gaussien", nous montrons, grâce à des techniques bayésiennes, que les vitesses minimax des espaces de Besov forts ou faibles sont les mêmes. Les distributions les plus défavorables que nous exhibons pour chaque espace de Besov faible sont construites à partir des lois de Pareto et diffèrent en cela de celles des espaces de Besov forts. Grâce aux simulations de ces distributions, nous construisons des représentations visuelles des "ennemis typiques". Enfin, nous exploitons ces distributions pour bâtir une procédure d'estimation minimax, de type "seuillage" appelée ParetoThresh, que nous étudions d'un point de vue pratique. Dans un deuxième temps, nous nous plaçons sous le modèle hétéroscédastique de bruit blanc gaussien et sous l'approche maxiset, nous établissons la sous-optimalité des estimateurs linéaires par rapport aux procédures adaptatives de type "seuillage". Puis, nous nous interrogeons sur la meilleure façon de modéliser le caractère "sparse" d'une suite à travers une approche bayésienne. À cet effet, nous étudions les maxisets des estimateurs bayésiens classiques - médiane, moyenne - associés à une modélisation construite sur des densités à queues lourdes. Les espaces maximaux pour ces estimateurs sont des espaces de Lorentz, et coïncident avec ceux associés aux estimateurs de type "seuillage". Nous prolongeons de manière naturelle ce résultat en obtenant une condition nécessaire et suffisante sur les paramètres du modèle pour que la loi a priori se concentre presque sûrement sur un espace de Lorentz précis.
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Lai, Mei Teng. "Airline operating cost estimation." Thesis, University of Macau, 2008. http://umaclib3.umac.mo/record=b1950305.
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Beek, Jaap van de. "Estimation of synchronization parameters." Licentiate thesis, Luleå tekniska universitet, Signaler och system, 1996. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-16971.
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This thesis deals with the estimation of synchronization parameters in {Orthogonal Frequency Division Multiplexing} (OFDM) communication systems and in active ultrasonic measuring systems. Estimation methods for the timing and frequency offset and for the attenuation taps of the frequency selective channel are presented and investigated.In OFDM communication systems the estimation of the timing offset of the transmitted data frame is one important parameter. This offset provides the receiver with a means of synchronizing its sampling clock to that of the transmitter. A second important parameter is the offset in the carrier frequency used by the receiver to demodulate the received signal.For OFDM systems using a cyclic prefix, the joint {Maximum Likelihood} (ML) estimation of the timing and carrier frequency offset is introduced. The redundancy introduced by the prefix is exploited optimally. This novel method is derived for a non-dispersive channel. Its performance, however, is also evaluated for a frequency-selective Rayleigh-fading radio channel. Time dispersion causes an irreducible error floor in this estimator's performance. This error floor is the limiting factor for the applicability of the timing estimator. Depending on the requirements, it may be used in either an acquisition or a tracking mode. For the frequency estimator the error floor is low enough to allow for stable frequency tracking.A low-complex variant of the timing offset estimator is presented allowing a simple implementation. This is the ML estimator, given a 2-bit representation of the received signal as the sufficient statistics. Its performance is evaluated for a frequency-selective Rayleigh-fading radio channel and for a twisted-pair copper channel. Simulations show this estimator to have a similar error floor as the full resolution ML estimator.The problem of estimating the propagation time of a signal is also of interest in active pulse echo systems, such as are used in, {\it e.g.}, radar, medical imaging, and geophysics. The {Minimum Mean Squared Error} (MMSE) estimator of arrival time is derived and investigated for an active airborne ultrasound measurement system. Besides performing better than the conventional {\it Maximum a Posteriori} (MAP) estimator, this method can be used to develop different estimators in situations where the system Signal to Noise Ratio (SNR) is unknown.Coherent multi-amplitude OFDM receivers generally need to compensate for a frequency selective channel in order to detect transmitted data symbols reliably. For this purpose, a channel equalizer needs to be fed estimates of the subchannel attenuations.The linear MMSE estimator of these attenuations is presented. Of all linear estimators, this estimator optimally makes use of the frequency correlation between the subchannel attenuations. Low-complex modified estimators are proposed and investigated. The proposed modifications cause an irreducible error floor for this estimator's performance, but simulations show that for SNR values up to 20~dB, the improvement of a modified estimator compared to the Least Squares (LS) estimator is at least 3~dB.Godkänd; 1996; 20080328 (ysko)
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Mahdi, Tahir Naweed. "Shrinkage estimation in prediction." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/mq30515.pdf.
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Yake, Bronson Thomas. "Self-Smoothing Functional Estimation." MSSTATE, 2002. http://sun.library.msstate.edu/ETD-db/theses/available/etd-09032002-090546/.
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Analysis of measured data is often required when there is no deep understanding of the mathematics that accurately describes the process being measured. Additionally, realistic estimation of the derivative of measured data is often useful. Current techniques of accomplishing this type of data analysis are labor intensive, prone to significant error, and highly dependent on the expertise of the engineer performing the analysis. The ?Self-Smoothing Functional Estimation? (SSFE) algorithm was developed to automate the analysis of measured data and to provide a reliable basis for the extraction of derivative information. In addition to the mathematical development of the SSFE algorithm, an example is included in Chapter III that illustrates several of the innovative features of the SSFE and associated algorithms. Conclusions are drawn about the usefulness of the algorithm from an engineering perspective and additional possible uses are mentioned.
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Jaganathan, Venkata Krishnan. "Robust motion estimation techniques." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/6032.
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Thesis (M.S.)--University of Missouri-Columbia, 2007.The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on April 15, 2008) Includes bibliographical references.
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Petzschner, Frederike Hermi. "Magnitude estimation in humans." Diss., lmu, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-155891.
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Sakarya, Fatma Ayhan. "Passive source location estimation." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/13714.
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