Dissertations / Theses on the topic 'Chaines de Markov'
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Sudyko, Elena. "Dollarisation finançière en Russie." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLE032.
Full textThis thesis develops a portfolio model of financial dollarization (FD) and estimates it for Russia. The contribution of this work will be to construct the first theoretical meanvariance-skewness-kurtosis model of financial dollarization and to validate it empirically. The work builds on previous research which found that adding higher moments, as Skewness and Kurtosis, to the minimum variance portfolio (MVP) enables a better modelling of portfolio choice, and develops such a model for FD. We then use Markovswitching methods on monthly data for bank deposits in Russia since the late 1990s to document the dominant influence of inflation and currency depreciation and their moments as the main determinants of deposit dollarization in a mean-varianceskewness-kurtosis framework during crisis as opposed to normal periods
Nunzi, Francois. "Autour de quelques chaines de Markov combinatoires." Thesis, Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCC270/document.
Full textWe consider two types of combinatoric Markov chains. We start with Juggling Markov chains, inspired from Warrington's model. We define multivariate generalizations of the existing models, for which we give stationary mesures and normalization factors with closed-form expressions. We also investigate the case where the maximum height at which the juggler may send balls tends to infinity. We then reformulate the Markov chain in terms of integer partitions, which allows us to consider the case where the juggler interacts with infinitely many balls. Our proofs are obtained through an enriched Markov chain on set partitions. We also show that one of the models has the ultrafast convergence property : the stationary mesure is reached after a finite number of steps. In the following Chapter, we consider multivariate generalizations of those models : the juggler now juggles with balls of different weights, and when a heavy ball collides with a lighter one, this light ball is bumped to a higher position, where it might collide with a lighter one, until a ball reaches the highest position. We give closed-form expressions for the stationary mesures and the normalization factors. The last Chapter is dedicated to the stochastic sandpile model, for which we give a proof for a conjecture set by Selig : the stationary mesure does not depend on the law governing sand grains additions
Aspandiiarov, Sanjar. "Quelques proprietes des chaines de markov et du mouvement brownien." Paris 6, 1994. http://www.theses.fr/1994PA066304.
Full textGiordana, Nathalie. "Segmentation non supervisee d'images multi-spectrales par chaines de markov cachees." Compiègne, 1996. http://www.theses.fr/1996COMP981S.
Full textVALLET, ROBERT. "Applications de l'identification des chaines de markov cachees aux communications numeriques." Paris, ENST, 1991. http://www.theses.fr/1991ENST0032.
Full textLADELLI, LUCIA. "Theoremes limites pour les chaines de markov : application aux algorithmes stochastiques." Paris 6, 1989. http://www.theses.fr/1989PA066283.
Full textBENMILOUD, BTISSAM. "Chaines de markov cachees et segmentation non supervisee de sequences d'images." Paris 7, 1994. http://www.theses.fr/1994PA077120.
Full textLezaud, Pascal. "Etude quantitative des chaines de markov par perturbation de leur noyau." Toulouse 3, 1998. https://hal-enac.archives-ouvertes.fr/tel-01084797.
Full textMeziane, Abdelouafi. "Quelques resultats nouveaux sur les mesures stationnaires de chaines de markov denombrables." Toulouse 3, 1987. http://www.theses.fr/1987TOU30252.
Full textEl, maalouf Joseph. "Méthodes de Monte Carlo stratifiées pour la simulation des chaines de Markov." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM089.
Full textMonte Carlo methods are probabilistic schemes that use computers for solving various scientific problems with random numbers. The main disadvantage to this approach is the slow convergence. Many scientists are working hard to find techniques that may accelerate Monte Carlo simulations. This is the aim of some deterministic methods called quasi-Monte Carlo, where random points are replaced with special sets of points with enhanced uniform distribution. These methods do not provide confidence intervals that permit to estimate the errordone. In the present work, we are interested with random methods that reduce the variance of a Monte Carlo estimator : the stratification techniques consist of splitting the sampling area into strata where random samples are chosen. We focus here on applications of stratified methods for approximating Markov chains, simulating diffusion in materials, or solving fragmentationequations.In the first chapter, we present Monte Carlo methods in the framework of numerical quadrature, and we introduce the stratification strategies. We focus on two techniques : the simple stratification (MCS) and the Sudoku stratification (SS), where the points repartitions are similar to Sudoku grids. We also present quasi-Monte Carlo methods, where quasi-random pointsshare common features with stratified points.The second chapter describes the use of stratified algorithms for the simulation of Markov chains. We consider time-homogeneous Markov chains with one-dimensional discrete or continuous state space. We establish theoretical bounds for the variance of some estimator, in the case of a discrete state space, that indicate a variance reduction with respect to usual MonteCarlo. The variance of MCS and SS methods is of order 3/2, instead of 1 for usual MC. The results of numerical experiments, for one-dimensional or multi-dimensional, discrete or continuous state spaces show improved variances ; the order is estimated using linear regression.In the third chapter, we investigate the interest of stratified Monte Carlo methods for simulating diffusion in various non-stationary physical processes. This is done by discretizing time and performing a random walk at every time-step. We propose algorithms for pure diffusion, for convection-diffusion, and reaction-diffusion (Kolmogorov equation or Nagumo equation) ; we finally solve Burgers equation. In each case, the results of numerical tests show an improvement of the variance due to the use of stratified Sudoku sampling.The fourth chapter describes a stratified Monte Carlo scheme for simulating fragmentation phenomena. Through several numerical comparisons, we can see that the stratified Sudoku sampling reduces the variance of Monte Carlo estimates. We finally test a method for solving an inverse problem : knowing the evolution of the mass distribution, it aims to find a fragmentation kernel. In this case quasi-random points are used for solving the direct problem
NASRO-ALLAH, ABDELAZIZ. "Simulation de chaines de markov et techniques de reduction de la variance." Rennes 1, 1991. http://www.theses.fr/1991REN10025.
Full textCottrell, Marie. "Modélisation de réseaux de neurones par des chaines de Markov et autres applications." Paris 11, 1988. http://www.theses.fr/1988PA112232.
Full textThe first part of the thesis consists of a paper published in IEEE Trans. Aut. Control (vol. AC-28, n°9, 1983), with J. C. Fort and G. Malgouyres. It gives two methods of calculating the exit time of a Markov chain from an attraction domain this time is extremely long, sa we use an exponential change of probability (that of large deviations theory), for a fast simulation and a non-standard approximation by diffusion. The second part includes two papers published with J. C. Fort in the Annales de l'IHP, Probabilités and Statistiques (vol. 23, n° 1, 1987}, and in Biological Cybernetics (n° 53, 1986). In the first one, we prove the convergence of Kohonen's self-organizing algorithm, in dimension 1. In the second one, we define another self-organizing algorithm, which is a simplified variant of Kohonen's, and we prove its convergence in dimensions 1 and 2. In the third part, published in Biological Cybernetics (n°58, 1988), we solve the problem of the connection matrix calculus for a Mac-Culloch or Hopfield neural network, so as to get the largest attractivity for the deterministic algorithm and non-orthogonal patterns. Then we calculate the attractivity of each memorized pattern, for a given connection matrix. The last part is devoted to the study of the role of inhibition in a nearest-neighbours-connected neural network. The model closely ressembles the biological reality of the young animal's cerebellar cortex. We prove that, when inhibition is smaller than a certain threshold, the network is ergodic and works in a stationary way. Conversely, when inhibition increases, striped or moiré responses appear, whose form and width depend on the considered neighbourhood size
Yahiaoui, Meriem. "Modèles statistiques avancés pour la segmentation non supervisée des images dégradées de l'iris." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL006/document.
Full textIris is considered as one of the most robust and efficient modalities in biometrics because of its low error rates. These performances were observed in controlled situations, which impose constraints during the acquisition in order to have good quality images. The renouncement of these constraints, at least partially, implies degradations in the quality of the acquired images and it is therefore a degradation of these systems’ performances. One of the main proposed solutions in the literature to take into account these limits is to propose a robust approach for iris segmentation. The main objective of this thesis is to propose original methods for the segmentation of degraded images of the iris. Markov chains have been well solicited to solve image segmentation problems. In this context, a feasibility study of unsupervised segmentation into regions of degraded iris images by Markov chains was performed. Different image transformations and different segmentation methods for parameters initialization have been studied and compared. Optimal modeling has been inserted in iris recognition system (with grayscale images) to produce a comparison with the existing methods. Finally, an extension of the modeling based on the hidden Markov chains has been developed in order to realize an unsupervised segmentation of the iris images acquired in visible light
BONHOURE, FRANCOIS. "Solution numerique de chaines de markov particulieres pour l'etude des systemes a evenements discrets." Paris 6, 1990. http://www.theses.fr/1990PA066414.
Full textMoreaux, Patrice. "Structuration des chaines de Markov des réseaux de Petri stochastiques : décomposition tensorielle et agrégation." Paris 9, 1996. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=1996PA090041.
Full textDubarry, Blandine. "Comportement asymptotique des systèmes de fonctions itérées et applications aux chaines de Markov d'ordre variable." Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1S114/document.
Full textThe purpose of this thesis is the study of the asymptotic behaviour of iterated function systems (IFS). In a first part, we will introduce the notions related to the study of such systems and we will remind different applications of IFS such as random walks on graphs or aperiodic tilings, random dynamical systems, proteins classification or else $q$-repeated measures. We will focus on two other applications : the chains of infinite order and the variable length Markov chains. We will give the main results in the literature concerning the study of invariant measures for IFS and those for the calculus of the Hausdorff dimension. The second part will be dedicated to the study of a class of iterated function systems (IFSs) with non-overlapping or just-touching contractions on closed real intervals and adapted piecewise constant transition probabilities. We give criteria for the existence and the uniqueness of an invariant probability measure for the IFSs and for the asymptotic stability of the system in terms of bounds of transition probabilities. Additionally, in case there exists a unique invariant measure and under some technical assumptions, we obtain its exact Hausdorff dimension as the ratio of the entropy over the Lyapunov exponent. This result extends the formula, established in the literature for continuous transition probabilities, to the case considered here of piecewise constant probabilities. The last part is dedicated to a special case of IFS : Variable Length Markov Chains (VLMC). We will show that under a weak non-nullness condition and continuity for the ultrametric distance of the transition probabilities, they admit a unique invariant measure which is attractive for the weak convergence
Ango, Nze Patrick. "Critères d'ergodicité de modèles markoviens : estimation non paramétrique sous des hypothèses de dépendance faible." Paris 9, 1994. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=1994PA090037.
Full textBrouard, Thierry. "Algorithmes hybrides d'apprentissage de chaines de Markov cachées : conception et applications à la reconnaissance des formes." Tours, 1999. http://www.theses.fr/1999TOUR4002.
Full textThe main point of this work is based on the quality of modelization of data (called observations) made by hidden Markov models (HMMs). Our goal is to propose algorithms that improve this quality. The criterion used to quantify the quality of HMM is the probability that a given model generates a given observation. To solve this problem, we use a genetic hybridization of HMM. Using genetic algorithms (GAs) jointly to HMM permits two things. First, GAs let us to explore more efficiently the set of models, avoiding local optima. Second, GAs optimize an important characteristic of HMM : its number of hidden states. The most efficient hybrid algorithm finds the best HMM for a given problem, by itself. This means that the GA designs a set of states and the associated transition probabilities. Many explications have been done in the framework of this thesis, in many domains like image recognition, time series prediction, unsupervised image segmentation and object tracking in sequences of images. The new algorithms proposed here are appliable to all domains (peovided that hypothesis related to HMM are satisfied). They allow a fast and efficient training of HMM, and an entirely automatic determination of the architecture (number of states, transition probabilities) of the HMM
DUFOUR, SANDRA. "Inference dynamique de chaines de markov cachees appliquee a la reconnaissance multilocuteur en milieu bruite." Rennes 1, 1998. http://www.theses.fr/1998REN10055.
Full textSAMSON, PAUL-MARIE. "Inegalites de concentration de la mesure pour des chaines de markov et des processus -melangeants." Toulouse 3, 1998. http://www.theses.fr/1998TOU30073.
Full textABDALLAH, HAISCAM. "Construction d'un logiciel de calcul des elements transitoires de chaines de markov a temps continu." Rennes 1, 1989. http://www.theses.fr/1989REN10055.
Full textRancurel, Thierry. "Modélisation des erreurs et capacité d'un canal avec évanouissement à l'aide de chaines de Markov." Toulouse, INPT, 2001. http://www.theses.fr/2001INPT049H.
Full textNuel, Grégory. "Grandes deviations et chaines de markov pour l'etude des occurrences de mots dans les sequences biologiques." Evry-Val d'Essonne, 2001. http://www.theses.fr/2001EVRY0006.
Full textMAILLARD, GREGORY. "Chaines a liaisons completes et mesures de Gibbs unidimensionnelles." Phd thesis, Université de Rouen, 2003. http://tel.archives-ouvertes.fr/tel-00005285.
Full textYahiaoui, Meriem. "Modèles statistiques avancés pour la segmentation non supervisée des images dégradées de l'iris." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLL006.
Full textIris is considered as one of the most robust and efficient modalities in biometrics because of its low error rates. These performances were observed in controlled situations, which impose constraints during the acquisition in order to have good quality images. The renouncement of these constraints, at least partially, implies degradations in the quality of the acquired images and it is therefore a degradation of these systems’ performances. One of the main proposed solutions in the literature to take into account these limits is to propose a robust approach for iris segmentation. The main objective of this thesis is to propose original methods for the segmentation of degraded images of the iris. Markov chains have been well solicited to solve image segmentation problems. In this context, a feasibility study of unsupervised segmentation into regions of degraded iris images by Markov chains was performed. Different image transformations and different segmentation methods for parameters initialization have been studied and compared. Optimal modeling has been inserted in iris recognition system (with grayscale images) to produce a comparison with the existing methods. Finally, an extension of the modeling based on the hidden Markov chains has been developed in order to realize an unsupervised segmentation of the iris images acquired in visible light
Guillotin-Plantard, Nadine. "Marche aleatoire dynamique dans une scene aleatoire. Problemes lies a l'inhomogeneite spatiale de certaines chaines de markov." Rennes 1, 1997. http://www.theses.fr/1997REN10107.
Full textEl, Ayoubi Salah Eddine. "Contrôle d'admission pour garantir la qualité de service dans les réseaux mobiles de troisième génération." Paris 6, 2004. http://www.theses.fr/2004PA066107.
Full textAndral, Charly. "Quelques contributions aux méthodes de Monte Carlo en statistique." Electronic Thesis or Diss., Université Paris sciences et lettres, 2024. http://www.theses.fr/2024UPSLD049.
Full textMonte Carlo methods are extensively utilized in statistics for estimating quantities that cannot be analytically. In this thesis, we investigate various approaches to enhance the efficiency of Monte Carlo methods and establish connections between different techniques.In the first part, we connect Markov chain Monte Carlo methods with rejection sampling and important sampling to propose a new algorithm, the Importance Markov Chain. For this algorithm, we provide a theoretical analysis of its convergence properties by establishing a law of large numbers, a central limit theorem and a geometric ergodicity result. We also provide a numerical study to illustrate the performance of the Importance Markov Chain.In the second part, we combine normalizing flows with randomized quasi-Monte Carlo methods to improve the convergence rate of the estimator. We test our method on some examples and show that it can outperform standard Monte Carlo methods on low dimensional problems. However, the performance of the method decays when the dimension of the problem increases.In the third and final part, we cover another class of Monte Carlo methods, the piecewise deterministic Markov processes. We propose a new algorithm to sample from these processes and provide a theoretical proof of the correctness of the method. We provide several numerical experiments to illustrate the performance of the algorithm. It outperforms other PMDPs sampling algorithms in terms of computational cost and robustness when the potential is not convex
Karelović, Bruno. "Quantitative analysis of stochastic systems : priority games and populations of Markov chains." Thesis, Sorbonne Paris Cité, 2017. http://www.theses.fr/2017USPCC165/document.
Full textThis thesis examines some quantitative questions in the framework of two different stochastic models. It is divided into two parts: the first part examines a new class of stochastic games with priority payoff. This class of games contains as proper subclasses the parity games extensively studied in computer science, and limsup and liminf games studied in game theory. The second part of the thesis examines some natural but involved questions about distributions, studied in the simple framework of finite state Markov chain.In the first part, we examine two-player zero-sum games focusing on a particular payoff function that we call the priority payoff. This payoff function generalizes the payoff used in parity games. We consider both turn-based stochastic priority games and concurrent priority games. Our approach to priority games is based on the concept of the nearest fixed point of monotone nonexpansive mappings and extends the mu-calculus approach to priority games.The second part of the thesis deals with population questions. Roughly speaking, we examine how a probability distribution over states evolves in time. More specifically, we are interested in questions like the following one: from an initial distribution, can the population reach at some moment a distribution with a probability mass exceeding a given threshold in state Goal? It turns out that this type of questions is much more difficult to handle than the questions concerning individual trajectories: it is not known for the simple model of Markov chains whether population questions are decidable. We study restrictions of Markov chains ensuring decidability of population questions
Combescure, Christophe. "Évaluation de nouvelles techniques diagnostiques en présence d'un gold standard imparfait et méta-analyses." Montpellier 1, 2003. http://www.theses.fr/2003MON1T016.
Full textKhebbab, Mohamed. "Contribution à l'étude du CND par Courants de Foucault de matériaux hétérogènes faiblement conducteurs à base d'éléments finis." Thesis, Nantes, 2016. http://www.theses.fr/2016NANT4056/document.
Full textThe work of this thesis consists in the investigation of characterization techniques and electromagnetic testing of composite materials, particularly the unidirectional CFRP ones (Carbon Fibers Reinforced Polymer). Two models are then developed. The first model that is intended for the characterization of the transverse electric conductivity of CFRP is based on percolation through resistor network. The physical parameters of the network make use of stochastic approaches (Markov chains). Besides predicting the transverse electrical conductivity of the material, the model allows us to understand the main parameters that influence the conductivity. The second model deals with the eddy current non-destructive testing of these materials by adopting an approach of parallel resolutions of micro and macro problems using the finite element heterogeneous multiscale method (FE-HMM). This model is relatively more accurate than the classical approach based on the homogenization techniques, and notably allows to characterize microscopic defects
Poly, Guillaume. "Formes de Dirichlet et applications en théorie ergodique des chaînes de Markov." Phd thesis, Université Paris-Est, 2011. http://tel.archives-ouvertes.fr/tel-00690724.
Full textDuchemin, Quentin. "Growth dynamics of large networks using hidden Markov chains." Thesis, Université Gustave Eiffel, 2022. https://tel.archives-ouvertes.fr/tel-03749513.
Full textThe first part of this thesis aims at introducing new models of random graphs that account for the temporal evolution of networks. More precisely, we focus on growth models where at each instant a new node is added to the existing graph. We attribute to this new entrant properties that characterize its connectivity to the rest of the network and these properties depend only on the previously introduced node. Our random graph models are thus governed by a latent Markovian dynamic characterizing the sequence of nodes in the graph. We are particularly interested in the Stochastic Block Model and in Random Geometric Graphs for which we propose algorithms to estimate the unknown parameters or functions defining the model. We then show how these estimates allow us to solve link prediction or collaborative filtering problems in networks.The theoretical analysis of the above-mentioned algorithms requires advanced probabilistic tools. In particular, one of our proof is relying on a concentration inequality for U-statistics in a dependent framework. Few papers have addressed this thorny question and existing works consider sets of assumptions that do not meet our needs. Therefore, the second part of this manuscript will be devoted to the proof of a concentration inequality for U-statistics of order two for uniformly ergodic Markov chains. In Chapter 5, we exploit this concentration result for U-statistics to make new contributions to three very active areas of Statistics and Machine Learning.Still motivated by link prediction problems in graphs, we study post-selection inference procedures in the framework of logistic regression with $L^1$ penalty. We prove a central limit theorem under the distribution conditional on the selection event and derive asymptotically valid testing procedures and confidence intervals
Mathieu, Eve. "Modélisations multi-états, markoviennes et semi-markoviennes : application à l'évolution de l'état de santé des patients atteints du virus du SIDA." Montpellier 1, 2005. http://www.theses.fr/2005MON1T008.
Full textPham, Thi Da Cam. "Théorèmes limite pour un processus de Galton-Watson multi-type en environnement aléatoire indépendant." Thesis, Tours, 2018. http://www.theses.fr/2018TOUR4005/document.
Full textThe theory of multi-type branching process in i.i.d. environment is considerably less developed than for the univariate case, and fundamental questions are up to date unsolved. Answers demand a solid understanding of the behavior of products of i.i.d. matrices with non-negative entries. Under mild assumptions, when the probability generating functions of the reproduction laws are fractional-linear, the survival probability of the multi-type branching process in random environment up to moment n is proportional to 1/√n as n → ∞. Techniques for univariate branching process in random environment and methods from the theory of products of i.i.d. random matrices are required
Boher, Jean-Marie. "Processus ponctuels et modèles markoviens : exemple d'application à une pathologie." Montpellier 1, 2001. http://www.theses.fr/2001MON1T019.
Full textEnfroy, Aurélien. "Contributions à la conception, l'étude et la mise en œuvre de méthodes de Monte Carlo par chaîne de Markov appliquées à l'inférence bayésienne." Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS012.
Full textThis thesis focuses on the analysis and design of Markov chain Monte Carlo (MCMC) methods used in high-dimensional sampling. It consists of three parts.The first part introduces a new class of Markov chains and MCMC methods. These methods allow to improve MCMC methods by using samples targeting a restriction of the original target distribution on a domain chosen by the user. This procedure gives rise to a new chain that takes advantage of the convergence properties of the two underlying processes. In addition to showing that this chain always targets the original target measure, we also establish ergodicity properties under weak assumptions on the Markov kernels involved.The second part of this thesis focuses on discretizations of the underdamped Langevin diffusion. As this diffusion cannot be computed explicitly in general, it is classical to consider discretizations. This thesis establishes for a large class of discretizations a condition of uniform minimization in the time step. With additional assumptions on the potential, it shows that these discretizations converge geometrically to their unique V-invariant probability measure.The last part studies the unadjusted Langevin algorithm in the case where the gradient of the potential is known to within a uniformly bounded error. This part provides bounds in V-norm and in Wasserstein distance between the iterations of the algorithm with the exact gradient and the one with the approximated gradient. To do this, an auxiliary Markov chain is introduced that bounds the difference. It is established that this auxiliary chain converges in distribution to sticky process already studied in the literature for the continuous version of this problem
Coq, Guilhelm. "Utilisation d'approches probabilistes basées sur les critères entropiques pour la recherche d'information sur supports multimédia." Poitiers, 2008. http://theses.edel.univ-poitiers.fr/theses/2008/Coq-Guilhelm/2008-Coq-Guilhelm-These.pdf.
Full textModel selection problems appear frequently in a wide array of applicative domains such as data compression and signal or image processing. One of the most used tools to solve those problems is a real quantity to be minimized called information criterion or penalized likehood criterion. The principal purpose of this thesis is to justify the use of such a criterion responding to a given model selection problem, typically set in a signal processing context. The sought justification must have a strong mathematical background. To this end, we study the classical problem of the determination of the order of an autoregression. . We also work on Gaussian regression allowing to extract principal harmonics out of a noised signal. In those two settings we give a criterion the use of which is justified by the minimization of the cost resulting from the estimation. Multiple Markov chains modelize most of discrete signals such as letter sequences or grey scale images. We consider the determination of the order of such a chain. In the continuity we study the problem, a priori distant, of the estimation of an unknown density by an histogram. For those two domains, we justify the use of a criterion by coding notions to which we apply a simple form of the “Minimum Description Length” principle. Throughout those application domains, we present alternative methods of use of information criteria. Those methods, called comparative, present a smaller complexity of use than usual methods but allow nevertheless a precise description of the model
Landelle, Benoît. "Etude statistique du problème de la trajectographie passive." Paris 11, 2009. http://www.theses.fr/2009PA112057.
Full textThis thesis presents a statistical study of the bearings-only tracking problem. In a first part, we deal with the question of observability for parametric and piecewise parametric trajectories and for constant speed trajectories. The second part is dedicated to the estimation: we give the properties of the maximum likelihood estimator for parametric and piecewise parametric trajectories. Even if good asymptotic properties hold, the non-robust behaviour of estimation is also described. The sensitivity of estimation is then studied when the state model is not completely specified. The cases of deterministic and stochastic state noise are considered in a semiparametric frame when the law of state noise is unknown. In the last part, we consider the bearings-only tracking problem as a hidden Markov Model. We focus on the study of the optimal filter and on its approximation by algorithmic methods. The extended Kalman filter is tested under different state noise conditions. We finally give asymptotic stability results for non-ergodic hidden Markov models and their application to bearings-only tracking
Ben, Arfa Nejla. "Changements structurels et dynamiques spatiales des exploitations laitières." Phd thesis, AgroParisTech, 2011. http://pastel.archives-ouvertes.fr/pastel-01057230.
Full textHuet, Fabrice. "Objets mobiles : conception d'un middleware et évaluation de la communication." Phd thesis, Université de Nice Sophia-Antipolis, 2002. http://tel.archives-ouvertes.fr/tel-00505420.
Full textChevallier, Thierry. "Intérêt médico-économique et stratégie d'utilisation d'un outil de pré-screening (OSIRIS®) dans le dépistage de l'ostéoporose chez les femmes ménopausées." Montpellier 1, 2002. http://www.theses.fr/2002MON1T015.
Full textDesmond-Le, Quéméner Elie. "A la recherche du dernier ancêtre commun aux eucaryotes : l'apport de la phylogénomique." Paris 7, 2009. http://www.theses.fr/2009PA077229.
Full textThe availability of many eukaryotic genomes opens, today, the opportunity to study their evolution using in silico methods. The aim of this thesis was to clarify several crucial steps of the origin and early evolution of eukaryotes through phylogenomics approaches focused on the analysis of cellular Systems. First, I have analysed the evolution of the mitochondrial ribosome. It allowed me to reconstruct the nature of the ancestral System present in the last eukaryotic common ancestor (the LECA) and gave important information about the timing of the endosymbiosis leading to mitochondria as well as the emergence of modem eukaryotes. It further showed that proteomic analysis of macromolecular complexes in a wider taxonomic sampling might provide important information for the global phylogeny of eukaryotes. Second, I have analysed the pathway for the synthesis of sterols, which are key components of eukaryotic membranes. My results indicate that the LECA was already capable of synthesizing sophisticated sterols and therefore lived in fully aerobic environments. It also indicates that this pathway is not of bacterial origin. Finally, I highlighted the existence of a reservoir of still unknown enzymes in diverse eukaryotic lineages. Third, I have studied the evolution of ionic pumps of the P-ATPases family, whose members are specific for different cellular compartments. This showed that the LECA likely already had a highly developed System of endomembranes. Moreover, I highlighted a number of cases of horizontal gene transfers between eukaryotes and showed how the expansion of gene families at the base of some lineages have paved the way for the development of multicellularity
Faraud, Gabriel. "Sur certains processus aléatoires en milieu aléatoire." Phd thesis, Université Paris-Nord - Paris XIII, 2010. http://tel.archives-ouvertes.fr/tel-00566478.
Full textMirabeau, Olivier. "Recherche de nouvelles hormones peptidiques codées par le génome humain." Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2008. http://tel.archives-ouvertes.fr/tel-00340710.
Full textGuibourg, Denis. "Théorèmes de renouvellement pour des fonctionnelles additives associées à des chaînes de Markov fortement ergodiques." Phd thesis, Université Rennes 1, 2011. http://tel.archives-ouvertes.fr/tel-00583175.
Full textVernet, Elodie Edith. "Modèles de mélange et de Markov caché non-paramétriques : propriétés asymptotiques de la loi a posteriori et efficacité." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS418/document.
Full textLatent models have been widely used in diverse fields such as speech recognition, genomics, econometrics. Because parametric modeling of emission distributions, that is the distributions of an observation given the latent state, may lead to poor results in practice, in particular for clustering purposes, recent interest in using non parametric latent models appeared in applications. Yet little thoughts have been given to theory in this framework. During my PhD I have been interested in the asymptotic behaviour of estimators (in the frequentist case) and the posterior distribution (in the Bayesian case) in two particuliar non parametric latent models: hidden Markov models and mixture models. I have first studied the concentration of the posterior distribution in non parametric hidden Markov models. More precisely, I have considered posterior consistency and posterior concentration rates. Finally, I have been interested in efficient estimation of the mixture parameter in semi parametric mixture models
Racoceanu, Daniel. "Contribution a la modelisation et a l'analyse des chaines de markov a echelles de temps et echelles de ponderations multiples. Application a la gestion d'un systeme hydro-energetique." Besançon, 1997. http://www.theses.fr/1997BESA2001.
Full textSaint, Pierre Philippe. "Modèles multi-états de type Markovien et application à l'asthme." Phd thesis, Université Montpellier I, 2005. http://tel.archives-ouvertes.fr/tel-00010146.
Full textSadek, Amr Fouad. "Estimation des processus markoviens avec application en fiabilité." Compiègne, 2003. http://www.theses.fr/2003COMP1466.
Full textMarkov processes are very relevant to study the reliability as an application to real world problems. Ln this thesis, two types of processes, Markov chains and Markov pro cesses are considered. We concern with the non-parametric estimation ofthe reliability and its measurements. We define estimators of reliability, availability, etc. The asymptotic properties of the proposed estimators are studied: strong uniform consistent and normality. Using the asymptotic properties results we construct the confidence intervals for reliability and its measurements. Illustrative examples are presented to explain the obtained results and to compare with the standard empirical estimators. The extension to the semi-Markovian processes relates to a point not Jet specifically discussed in the literature, the estimation of the stationary distribution of semi- Mar kovian processes. We propose a new index for quality of life and discuss it through discrete and continuous time Markov process mode