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Lacour, Claire. "Estimation non paramétrique adaptative pour les chaînes de Markov et les chaînes de Markov cachées". Phd thesis, Université René Descartes - Paris V, 2007. http://tel.archives-ouvertes.fr/tel-00180107.
Pełny tekst źródłaBarbu, Vlad. "Estimation des chaînes semi-markoviennes et des chaînes semi-markoviennes cachées en vue d'applications en fiabilité et en biologie". Compiègne, 2005. http://www.theses.fr/2005COMP1568.
Pełny tekst źródłaThe first part of my thesis concerns the discrete time semi-Markov models and the associated nonparametric estimation. The obtained results are used for deriving estimators of the systems reliability and of the associated measures. The asymptotic properties of the estimators are studied. An example illustrates how to practically compute the reliability indicators. The second part of my thesis is devoted to the estimation of hidden semi-Markov models. The asymptotic properties of the estimators are studied and an EM algorithm is proposed. An application in genetics for detecting the CpG islands in a DNA sequence shows the interest of our researches
RAFI, Selwa. "Chaînes de Markov cachées et séparation non supervisée de sources". Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00995414.
Pełny tekst źródłaRafi, Selwa. "Chaînes de Markov cachées et séparation non supervisée de sources". Thesis, Evry, Institut national des télécommunications, 2012. http://www.theses.fr/2012TELE0020/document.
Pełny tekst źródłaThe restoration problem is usually encountered in various domains and in particular in signal and image processing. It consists in retrieving original data from a set of observed ones. For multidimensional data, the problem can be solved using different approaches depending on the data structure, the transformation system and the noise. In this work, we have first tackled the problem in the case of discrete data and noisy model. In this context, the problem is similar to a segmentation problem. We have exploited Pairwise and Triplet Markov chain models, which generalize Hidden Markov chain models. The interest of these models consist in the possibility to generalize the computation procedure of the posterior probability, allowing one to perform bayesian segmentation. We have considered these methods for two-dimensional signals and we have applied the algorithms to retrieve of old hand-written document which have been scanned and are subject to show through effect. In the second part of this work, we have considered the restoration problem as a blind source separation problem. The well-known "Independent Component Analysis" (ICA) method requires the assumption that the sources be statistically independent. In practice, this condition is not always verified. Consequently, we have studied an extension of the ICA model in the case where the sources are not necessarily independent. We have introduced a latent process which controls the dependence and/or independence of the sources. The model that we propose combines a linear instantaneous mixing model similar to the one of ICA model and a probabilistic model on the sources with hidden variables. In this context, we show how the usual independence assumption can be weakened using the technique of Iterative Conditional Estimation to a conditional independence assumption
Rouan, Lauriane. "Apports des chaînes de Markov cachées à l'analyse de données de capture-recapture". Montpellier 2, 2007. http://www.theses.fr/2007MON20188.
Pełny tekst źródłaParis, Sébastien. "Extraction Automatique de Pistes Fréquentielles en Sonar Passif par Chaînes de Markov Cachées". Toulon, 2000. http://www.theses.fr/2000TOUL0013.
Pełny tekst źródłaThe frequency vs. Time image called lofargram in any passive sonar system is the key of the downstream information processing : the operator will investigate on this representation in order to classify the tar¬gets of interest and/or to track the targets that have generated them by the so-called Target Motion Analysis (TMA). Both need to use frequency lines. For TMA, constant but Doppler-shifted frequencies are necessary. Conversely, for classification, the fluctuations of frequency help the discrimination between targets. In this thesis, we are concerned by unstable frequency line tracker (FLT). The role of such a tracker is to estimate frequency lines. The fundamental problems of FLT come from the unknown num¬ber of lines, their dates of birth and death, their respective SNR's and the case of crossing lines. We propose a method based on Markov Chain modeling : each frequency line is assumed to follow a random walk; the state space is the lofargram frequency cell set vs. A discrete and finite set of slopes. The data are composed by each lofargram line. When one unique line is present, we propose a scaled version of algorithms encountered in Hidden Markov Models (HMM) literature : Viterbi algorithm (VA), Forward (F), Forward-Backward (FB). In case of several frequency lines, we derive a new scaled FB algorithm in which each probability is conditioned by the exclusive event : two lines cannot be simultaneously in the same spot. The algorithm works in two passes : first, the lines are extracted from the beginning to the end of the lofargram; then, we estimate the dates of birth and death of each of them. When those dates are equal, the line is discarded. Therefore, the number of lines must be a priori overestimated. Trials on synthetic but also real data have been conducted and allow us to conclude that this algorithm performs very correctly (in a operational sense)
Lapuyade-Lahorgue, Jérôme. "Sur diverses extensions des chaînes de Markov cachées avec application au traitement des signaux radar". Phd thesis, Institut National des Télécommunications, 2008. http://tel.archives-ouvertes.fr/tel-00473711.
Pełny tekst źródłaFernandes, Clément. "Chaînes de Markov triplets et segmentation non supervisée d'images". Electronic Thesis or Diss., Institut polytechnique de Paris, 2022. http://www.theses.fr/2022IPPAS019.
Pełny tekst źródłaHidden Markov chains (HMC) are widely used in unsupervised Bayesian hidden discrete data restoration. They are very robust and, in spite of their simplicity, they are sufficiently efficient in many situations. In particular for image segmentation, despite their mono-dimensional nature, they are able, through a transformation of the bi-dimensional images into mono-dimensional sequences with Peano scan (PS), to give satisfying results. However, sometimes, more complex models such as hidden Markov fields (HMF) may be preferred in spite of their increased time complexity, for their better results. Moreover, hidden Markov models (the chains as well as the fields) have been extended to pairwise and triplet Markov models, which can be of interest in more complex situations. For example, when sojourn time in hidden states is not geometrical, hidden semi-Markov (HSMC) chains tend to perform better than HMC, and such is also the case for hidden evidential Markov chains (HEMC) when data are non-stationary. In this thesis, we first propose a new triplet Markov chain (TMC), which simultaneously extends HSMC and HEMC. Based on hidden triplet Markov chains (HTMC), the new hidden evidential semi-Markov chain (HESMC) model can be used in unsupervised framework, parameters being estimated with Expectation-Maximization (EM) algorithm. We validate its interest through some experiments on synthetic data. Then we address the problem of mono-dimensionality of the HMC with PS model in image segmentation by introducing the “contextual” Peano scan (CPS). It consists in associating to each index in the HMC obtained from PS, two observations on pixels which are neighbors of the pixel considered in the image, but are not its neighbors in the HMC. This gives three observations on each point of the Peano scan, which leads to a new conditional Markov chain (CMC) with a more complex structure, but whose posterior law is still Markovian. Therefore, we can apply the usual parameter estimation method: Stochastic Expectation-Maximization (SEM), as well as study unsupervised segmentation Marginal Posterior Mode (MPM) so obtained. The CMC with CPS based supervised and unsupervised MPM are compared to the classic scan based HMC-PS and the HMF through experiments on artificial images. They improve notably the former, and can even compete with the latter. Finally, we extend the CMC-CPS to Pairwise Conditional Markov (CPMC) chains and two particular triplet conditional Markov chain: evidential conditional Markov chains (CEMC) and conditional semi-Markov chains (CSMC). For each of these extensions, we show through experiments on artificial images that these models can improve notably their non conditional counterpart, as well as the CMC with CPS, and can even compete with the HMF. Beside they allow the generality of markovian triplets to better play its part in image segmentation, while avoiding the substantial time complexity of triplet Markov fields
Ben, Mabrouk Mohamed. "Modèles de Markov triplets en restauration des signaux". Phd thesis, Institut National des Télécommunications, 2011. http://tel.archives-ouvertes.fr/tel-00694128.
Pełny tekst źródłaDridi, Noura. "Estimation aveugle de chaînes de Markov cachées simples et doubles : Application au décodage de codes graphiques". Thesis, Evry, Institut national des télécommunications, 2012. http://www.theses.fr/2012TELE0022.
Pełny tekst źródłaSince its birth, the technology of barcode is well investigated for automatic identification. When reading, a barcode can be degraded by a blur , caused by a bad focalisation and/ or a camera movement. The goal of this thesis is the optimisation of the receiver of 1D and 2D barcode from hidden and double Markov model and blind statistical estimation approaches. The first phase of our work consists of modelling the original image and the observed one using Hidden Markov model. Then, new algorithms for joint blur estimation and symbol detection are proposed, which take into account the non-stationarity of the hidden Markov process. Moreover, a method to select the most relevant model of the blur is proposed, based on model selection criterion. The method is also used to estimate the blur length. Finally, a new algorithm based on the double Markov chain is proposed to deal with digital communication through a long memory channel. Estimation of such channel is not possible using the classical detection algorithms based on the maximum likelihood due to the prohibitive complexity. New algorithm giving good trade off between complexity and performance is provided
Vandekerkhove, Pierre. "Identification de l'ordre des processus ARMA stables : contribution à l'étude statistique des chaînes de Markov cachées". Montpellier 2, 1997. http://www.theses.fr/1997MON20115.
Pełny tekst źródłaNicolas, Pierre. "Mise au point et utilisation de modèles de chaînes de Markov cachées pour l'étude des séquences d'ADN". Evry-Val d'Essonne, 2003. http://www.theses.fr/2003EVRY0017.
Pełny tekst źródłaConsidering the use of self-training approaches, we developed in this thesis three domains in which we applied HMM for the bacterial genome interpretation. First, a segmentation method of DNA sequences into regions of homogeneous composition enables us to identify horizontal gene transfers on the Bacillus subtilis chromosome and also others heterogeneities levels linked to biological properties of genes. Next we developed a gene prediction software and we especially focused on small genes research. Around 30 genes smaller than 50 amino acids have been added to about 20 small genes previously biologically identified on B. Subtilis. Then we proposed a MCMC algorithm for Bayesian model selection in the context of RNA polymerase binding sites modeling
Trevezas, Samis. "Etude de l'estimation du Maximum de Vraisemblance dans des modèles Markoviens, Semi-Markoviens et Semi-Markoviens Cachés avec Applications". Phd thesis, Université de Technologie de Compiègne, 2008. http://tel.archives-ouvertes.fr/tel-00472644.
Pełny tekst źródłaTrevezas, Samis. "Etude de l'estimation du maximum de vraisemblance dans des modèles markoviens, semi-markoviens et semi-markoviens cachés avec applications". Phd thesis, Compiègne, 2008. http://www.theses.fr/2008COMP1772.
Pełny tekst źródłaWe construct the maximum likehood estimator (MLE) of the stationnary distribution an of the asymptotic variance of the central limit theorem for additive functionals of ergodic Markov chains and we prove its strong consistency and its asymptotic normamlity. In the sequel, we consider a non-parametric semi-Markov model. We present the exact MLE of the semi-Markov kernel that governs the evolution of the semi-Markov chain (SMC) and we prove the strong consistency as well as the asymptotic normality of every finite subvector of this estimator by obtaining explicit forms for the asymptotic covariance matrices. The asymptotics were considered for one trajectory of SMC as well as for a sequence of i. D. D. Observations of a SMC censored at a fixed time. We introduce a general hidden semi-Markov model (HSMM) with backward recurrence time dependence. We prove asymptotic properties of the MLE that corresponds to this model. We also deduce explicit expressions for the asymptotic covariance matrices that appear in the CLT for the MLE of some basic characteristics of the SMC. Finally, we propose an improved version of the EM algorithm for HSMM and a stochastic version of this algorithm (SAEM), in order to find the MLE for non-parametric HSMMs. Numerical examples are presented for both algorithms
Bercu, Sophie. "Modélisation stochastique du signal écrit par chaînes de Markov cachées : application à la reconnaissance automatique de l'écriture manuscrite". Rennes 1, 1994. http://www.theses.fr/1994REN10115.
Pełny tekst źródłaDapzol, N. "Analyse de l'activité de conduite par les chaînes de Markov cachées et les modèles de ruptures multi-phasiques: méthodologie et applications". Phd thesis, Université Claude Bernard - Lyon I, 2006. http://tel.archives-ouvertes.fr/tel-00543729.
Pełny tekst źródłaBrunel, Nicolas. "Sur quelques extensions des chaînes de Markov cachées et couples : application à la segmentation non supervisée de signaux radar". Paris 6, 2005. https://tel.archives-ouvertes.fr/tel-00011302.
Pełny tekst źródłaBrunel, Nicolas. "Sur quelques extensions des chaînes de Markov cachées et couples. Applications à la segmentation non-supervisée de signaux radar". Phd thesis, Université Pierre et Marie Curie - Paris VI, 2005. http://tel.archives-ouvertes.fr/tel-00011302.
Pełny tekst źródłaMuri, Florence. "Comparaison d'algorithmes d'identification de chaînes de Markov cachées et application a la détection de régions homogènes dans les séquences d'ADN". Paris 5, 1997. http://www.theses.fr/1997PA05S008.
Pełny tekst źródłaGarivier, Aurélien. "Modèles contextuels et alphabets infinis en théorie de l'information". Paris 11, 2006. http://www.theses.fr/2006PA112192.
Pełny tekst źródłaThis thesis explores some contemporary aspects of information theory, from source coding to issues of model selection. We first consider the problem of coding memoryless sources on a countable, infinite alphabet. As it is impossible to provide a solution which is both efficient and general, two approaches are considered: we first establish conditions under which the entropic rate can be reached, and we consider restricted classes for which tail probabilities are controlled. The second approach does not set any condition on the sources but provides a partial solution by coding only a part of the information - the pattern - which captures the repetitions in the message. In order to study more complex processes, we come back to the case of finite memory sources on a finite alphabet : it has given rise to many works and efficient algorithms like the Context Tree Weighting (CTW) Method. We show here that this method is also efficient on anon-parametric class of infinite memory sources: the renewal processes. We show then that the ideas on which CTW is based lead to a consistent estimator of the memory structure of a process, when this structure is finite. In fact, we complete the study of the BIC context tree estimator for Variable Length Markov Chains. In the last part, it is shown how similar ideas can be generalized for more complex sources on a (countable or not) infinite alphabet. We obtain consistent estimators for the order of hidden Markov models with Poisson and Gaussian emission
Abbassi, Noufel. "Chaînes de Markov triplets et filtrage optimal dans les systemes à sauts". Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00873630.
Pełny tekst źródłaRynkiewicz, Joseph. "Modèles hybrides intégrant des réseaux de neurones artificiels à des modèles de chaînes de Markov cachées : application à la prédiction de séries temporelles". Paris 1, 2000. http://www.theses.fr/2000PA010077.
Pełny tekst źródłaRichard, Hugues. "Prédiction de la localisation cellulaire des protéines à l'aide de leurs séquences biologiques". Phd thesis, Université d'Evry-Val d'Essonne, 2005. http://tel.archives-ouvertes.fr/tel-00011707.
Pełny tekst źródłaAinsi la majorité de ce travail de thèse s'intéresse au problème de la prédiction du compartiment cellulaire d'une protéine à partir de sa séquence primaire.
Nous nous sommes attachés à proposer des alternatives descriptives aux méthodes existantes de prédiction de la localisation cellulaire en utilisant : (1) de nouveaux descripteurs issus de la séquence nucléique, (2) une approche par chaînes de Markov cachées (CMC) et arbres de décision. L'approche par CMC est justifiée biologiquement a posteriori car elle permet la modélisation de signaux d'adressage conjointement à la prise en compte de la composition globale. En outre, l'étape de classification hiérarchique par arbre améliore nettement les résultats de classification. Les résultats obtenues lors des comparaisons avec les méthodes existantes et utilisant des descripteurs fondés sur la composition globale possèdent des performances similaires.
Votsi, Irène. "Evaluation des risques sismiques par des modèles markoviens cachés et semi-markoviens cachés et de l'estimation de la statistique". Thesis, Compiègne, 2013. http://www.theses.fr/2013COMP2058.
Pełny tekst źródłaThe first chapter describes the definition of the subject under study, the current state of science in this area and the objectives. In the second chapter, continuous-time semi-Markov models are studied and applied in order to contribute to seismic hazard assessment in Northern Aegean Sea (Greece). Expressions for different important indicators of the semi- Markov process are obtained, providing forecasting results about the time, the space and the magnitude of the ensuing strong earthquake. Chapters 3 and 4 describe a first attempt to model earthquake occurrence by means of discrete-time hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs), respectively. A nonparametric estimation method is followed by means of which, insights into features of the earthquake process are provided which are hard to detect otherwise. Important indicators concerning the levels of the stress field are estimated by means of the suggested HMM and HSMM. Chapter 5 includes our main contribution to the theory of stochastic processes, the investigation and the estimation of the discrete-time intensity of the hitting time (DTIHT) for the first time referring to semi-Markov chains (SMCs) and hidden Markov renewal chains (HMRCs). A simple formula is presented for the evaluation of the DTIHT along with its statistical estimator for both SMCs and HMRCs. In addition, the asymptotic properties of the estimators are proved, including strong consistency and asymptotic normality. In chapter 6, a comparison between HMMs and HSMMs in a Markov and a semi-Markov framework is given in order to highlight possible differences in their stochastic behavior partially governed by their transition probability matrices. Basic results are presented in the general case where specific distributions are assumed for sojourn times as well as in the special case concerning the models applied in the previous chapters, where the sojourn time distributions are estimated non-parametrically. The impact of the differences is observed through the calculation of the mean value and the variance of the number of steps that the Markov chain (HMM case) and the EMC (HSMM case) need to make for visiting for the first time a particular state. Finally, Chapter 7 presents concluding remarks, perspectives and future work
Charantonis, Anastase Alexandre. "Méthodologie d'inversion de données océaniques de surface pour la reconstitution de profils verticaux en utilisant des chaînes de Markov cachées et des cartes auto-organisatrices". Paris 6, 2013. http://www.theses.fr/2013PA066761.
Pełny tekst źródłaSatellite observations provide us with the values of different biogeochemical parameters at the surface layer of the ocean. These observations are highly correlated with the underlying vertical profiles of different oceanic parameters, such as the Chlorophyll-A concentration, the salinity and temperature of the water column… The sea-surface data and the vertical profiles of the oceanic parameters constitute multi-dimensional vectors. Due to their multi-dimensionality and the high complexity of the dynamics connecting these data sets, their links cannot be modeled linearly. In this thesis we present a methodology to statistically invert sea-surface observations in order to retrieve these vertical profiles. The developed methodology, named PROFHMM, makes use of Self Organizing Maps in order to render the inversion problem compatible with the Hidden Markov Model formalism. PROFHMM makes full use of the topological aspect of the Self Organizing Maps in order not only to generate the topology and states of the Hidden Markov Model, but also improve the estimation of the probabilities essential to the accuracy of the model. The use of the Self Organizing maps was essential in obtaining the results for the geophysical applications of PROFHMM presented in this manuscript. The manuscript was structured in three chapters, each consisting of an article. In the first one, the general methodology of PROFHMM is developed, then tested for the retrieval of vertical profiles of Chlorophyll-A by inverting sea-surface observations. This application demonstrated the ability to synchronize sea-surface data with the output data of numerical models. The second article presents the application of PROFHMM on the inversion of sea-surface data obtained from the AVISO and NOAA projects, in order to retrieve the vertical profiles of temperature over the rail of the ARAMIS mission. The performances obtained demonstrate the ability of PROFHMM to synchronize sea-surface data with in-situ measurements. Finally, in the third article, we present a modification to the Viterbi Algorithm in order to take into account an à priori knowledge of the quality of the observations when performing reconstructions. The proposed methodology, named PROFHMM_UNC, was applied for the reconstruction of the temporal evolution of sea-surface data, by taking into account the quality of the satellite observations used. The validity of the method was proven by performing a twin experiment on the outputs of a numerical model
Boudaren, Mohamed El Yazid. "Modèles graphiques évidentiels". Phd thesis, Institut National des Télécommunications, 2014. http://tel.archives-ouvertes.fr/tel-01004504.
Pełny tekst źródłaPudlo, Pierre. "Estimations précises de grandes déviations et applications à la statistique des séquences biologiques". Phd thesis, Université Claude Bernard - Lyon I, 2004. http://tel.archives-ouvertes.fr/tel-00008517.
Pełny tekst źródłaGreau-Hamard, Pierre-Samuel. "Contribution à l’apprentissage non supervisé de protocoles pour la couche de Liaison de données dans les systèmes communicants, à l'aide des Réseaux Bayésiens". Thesis, CentraleSupélec, 2021. http://www.theses.fr/2021CSUP0009.
Pełny tekst źródłaThe world of telecommunications is rapidly developing, especially in the area of the Internet of Things; in such a context, it would be useful to be able to analyze any unknown protocol one might encounter. For this purpose, obtaining the state machine and frame formats of the target protocol is essential. These two elements can be extracted from network traces and/or execution traces using Protocol Reverse Engineering (PRE) techniques.By analyzing the performance of three algorithms used in PRE systems, we discovered the potential of models based on Bayesian networks. We then developed Bayesian Network Frame Format Finder (BaNet3F), our own frame format learning model based on Bayesian networks, and showed that its performance is significantly better than the state of the art. BaNet3F also includes an optimized version of the Viterbi algorithm, applicable to any Bayesian network, thanks to its ability to generate the necessary Markov boundaries itself
Boudaren, Mohamed El Yazid. "Modèles graphiques évidentiels". Electronic Thesis or Diss., Evry, Institut national des télécommunications, 2014. http://www.theses.fr/2014TELE0001.
Pełny tekst źródłaHidden Markov chains (HMCs) based approaches have been shown to be efficient to resolve a wide range of inverse problems occurring in image and signal processing. In particular, unsupervised segmentation of data is one of these problems where HMCs have been extensively applied. According to such models, the observed data are considered as a noised version of the requested segmentation that can be modeled through a finite Markov chain. Then, Bayesian techniques such as MPM can be applied to estimate this segmentation even in unsupervised way thanks to some algorithms that make it possible to estimate the model parameters from the only observed data. HMCs have then been generalized to pairwise Markov chains (PMCs) and triplet Markov chains (TMCs), which offer more modeling possibilities while showing comparable computational complexities, and thus, allow to consider some challenging situations that the conventional HMCs cannot support. An interesting link has also been established between the Dempster-Shafer theory of evidence and TMCs, which give to these latter the ability to handle multisensor data. Hence, in this thesis, we deal with three challenging difficulties that conventional HMCs cannot handle: nonstationarity of the a priori and/or noise distributions, noise correlation, multisensor information fusion. For this purpose, we propose some original models in accordance with the rich theory of TMCs. First, we introduce the M-stationary noise- HMC (also called jumping noise- HMC) that takes into account the nonstationary aspect of the noise distributions in an analogous manner with the switching-HMCs. Afterward, ML-stationary HMC consider nonstationarity of both the a priori and/or noise distributions. Second, we tackle the problem of non-stationary PMCs in two ways. In the Bayesian context, we define the M-stationary PMC and the MM-stationary PMC (also called switching PMCs) that partition the data into M stationary segments. In the evidential context, we propose the evidential PMC in which the realization of the hidden process is modeled through a mass function. Finally, we introduce the multisensor nonstationary HMCs in which the Dempster-Shafer fusion has been used on one hand, to model the data nonstationarity (as done in the hidden evidential Markov chains) and on the other hand, to fuse the information provided by the different sensors (as in the multisensor hidden Markov fields context). For each of the proposed models, we describe the associated segmentation and parameters estimation procedures. The interest of each model is also assessed, with respect to the former ones, through experiments conducted on synthetic and real data
Baysse, Camille. "Analyse et optimisation de la fiabilité d'un équipement opto-électrique équipé de HUMS". Phd thesis, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00986112.
Pełny tekst źródłaHuet, Alexis. "Méthodes particulaires et vraisemblances pour l'inférence de modèles d'évolution avec dépendance au contexte". Phd thesis, Université Claude Bernard - Lyon I, 2014. http://tel.archives-ouvertes.fr/tel-01058827.
Pełny tekst źródłaYahiaoui, 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.
Pełny tekst źródłaIris 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
Finkler, Audrey. "Modèle d'évolution avec dépendance au contexte et Corrections de statistiques d'adéquation en présence de zéros aléatoires". Phd thesis, Université de Strasbourg, 2010. http://tel.archives-ouvertes.fr/tel-00490844.
Pełny tekst źródłaYahiaoui, 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.
Pełny tekst źródłaIris 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
Chaubert, Florence. "Combinaisons markoviennes et semi-markoviennes de modèles de régression : application à la croissance d'arbres forestiers". Montpellier 2, 2008. http://www.theses.fr/2008MON20117.
Pełny tekst źródłaThis work focuses on Markov and semi-Markov switching regression models, i. E. Finite mixtures of regression models with (semi-)Markovian dependencies. These statistical models enable to analyse data structured as a succession of stationary phases that are asynchronous between individuals, influenced by time-varying covariates and which present inter-individual heterogeneity. The proposed inference algorithm for (semi-)Markov switching generalized linear models is a gradient EM algorithm. For (semi-)Markov switching linear mixed models, we propose MCEM-like algorithms whose E-step decomposes into two conditional restoration steps: one for the random effects given the state sequences (and the observed data) and one for the state sequences given the random effects (and the observed data). Various conditional restoration steps are presented. We study two types of random effects: individual-wise random effects and environmental random effects. The relevance of these models is illustrated by the analysis of forest tree growth influenced by climatic covariates. These models allow us to identify and characterize the three main growth components (ontogenetic component, environmental component and individual component). We show that the weight of each component varies according to species and silvicultural interventions
Lefèvre, Sébastien. "Détection d'événements dans une séquence vidéo". Phd thesis, Université François Rabelais - Tours, 2002. http://tel.archives-ouvertes.fr/tel-00278073.
Pełny tekst źródłaMattrand, Cécile. "Approche probabiliste de la tolérance aux dommages". Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2011. http://tel.archives-ouvertes.fr/tel-00738947.
Pełny tekst źródłaMartin, Juliette. "Prédiction de la structure locale des protéines par des modèles de chaîne de Markov cachées". Paris 7, 2005. http://www.theses.fr/2005PA077154.
Pełny tekst źródłaChaubert-Pereira, Florence. "Combinaisons markoviennes et semi-markoviennes de modèles de régression. Application à la croissance d'arbres forestiers". Phd thesis, Université Montpellier II - Sciences et Techniques du Languedoc, 2008. http://tel.archives-ouvertes.fr/tel-00341822.
Pełny tekst źródłaMercier, Fabien. "Cinq essais dans le domaine monétaire, bancaire et financier". Thesis, Paris 2, 2014. http://www.theses.fr/2014PA020065.
Pełny tekst źródłaThe thesis studies various themes that are central to modern finance : economic agents rationality and behavioural biases with respect to nominal values, the problem of asset fundamental valuation, the changing landscape of the European post-trade industry catalysed by the Eurosystem project Target 2 Securities, and models of defaults and methods to estimate defaults cycles for a given sector. Techniques employed vary: studies on individual data,econometrics, game theory, graph theory, Monte-Carlo simulations and hidden Markov chains. Concerning monetary illusion, results confirm those of previous study while emphasizing new areas for investigation concerning the interplay of individual characteristics, such as university education, and money illusion. The study of the Fed model shows that the long term relationship assumed between nominal government bond yield and dividend yield is neither robust, nor useful for reduced time horizons. The default model based on hidden Markov chains estimation gives satisfactory results in a European context, and this besides the relative scarcity of data used for its calibration
Matias, Catherine. "Estimation dans des modèles à variables cachées". Phd thesis, Université Paris Sud - Paris XI, 2001. http://tel.archives-ouvertes.fr/tel-00008383.
Pełny tekst źródłaBen, Ammar Hamza. "On models for performance evaluation and cache resources placement in multi-cache networks". Thesis, Rennes 1, 2019. http://www.theses.fr/2019REN1S006/document.
Pełny tekst źródłaIn the last few years, Content Providers (CPs) have experienced a high increase in requests for video contents and rich media services. In view of the network scaling limitations and beyond Content Delivery Networks (CDNs), Internet Service Providers (ISPs) are developing their own caching systems in order to improve the network performance. These factors explain the enthusiasm around the Content-Centric Networking (CCN) concept and its in-network caching feature. The analytical quantification of caching performance is, however, not sufficiently explored in the literature. Moreover, setting up an efficient caching system within a network infrastructure is very complex and remains an open problem. To address these issues, we provide first in this thesis a fairly generic and accurate model of caching nodes named MACS (Markov chain-based Approximation of Caching Systems) that can be adapted very easily to represent different caching schemes and which can be used to compute different performance metrics of multi-cache networks. We tackled after that the problem of cache resources allocation in cache-enabled networks. By means of our analytical tool MACS, we present an approach that solves the trade-off between different performance metrics using multi-objective optimization and we propose an adaptation of the metaheuristic GRASP to solve the optimization problem
Le, Coz Sebastian. "Modélisation de la dynamique des adventices dans un agroécosystème". Thesis, Toulouse 3, 2019. http://www.theses.fr/2019TOU30034.
Pełny tekst źródłaMany species have a dormant stage in their life cycle, such as seeds for plants. These species have different types of survival strategies. In particular, plants are known have survival strategies dependent on dormancy and dispersal of seeds. The metapopulation model, which does not consider a dormancy stage and is often used to analyse a species' dynamic, applied to a species which undergoes dormancy can lead to wrongly declare extinction in a patch where dormant individuals can still be present. In order to include dormancy in a model it is preferable to use hidden variables to model dormant individuals as they are often unobservable. Several Markovian models with hidden variables have already been proposed to study species with hidden stages. However, they all have different limitations : only presence/absence observations are modelled ; the dormancy stage is limited to one year or colonisation from neighbour patches is not taken into account. We propose a hidden Markov model with data feedback which describes the local and regional dynamics of a species with hidden stages where only observables stages may influence other patchs. The model allows species to undergo potentially time infinite dormancy using abundance classes. One would expect estimation, restoration and prediction of the next non-dormant populations to have an exponential computational time in terms of patches, however we have demonstrated that estimation, restoration and prediction are all achievable in a linear in terms of patches. The regional dynamic is modeled using the indistinguishable influence of neighbour non-dormant populations states on a dormant or non-dormant population. Numerical experiments on simulated data show that the state dormant populations can easily be retrieved as well as the future non-dormant populations' state. Results on weed species highlight that the state of the seed bank is mostly influenced by seed survival. Our framework provides a simple and efficient tool that could be further exploited to analyse and compare annual plants' dynamics, like weeds survival strategies in crop fields and even for species with hidden stages
Sekhi, Ikram. "Développement d'un alphabet structural intégrant la flexibilité des structures protéiques". Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCC084/document.
Pełny tekst źródłaThe purpose of this PhD is to provide a Structural Alphabet (SA) for more accurate characterization of protein three-dimensional (3D) structures as well as integrating the increasing protein 3D structure information currently available in the Protein Data Bank (PDB). The SA also takes into consideration the logic behind the structural fragments sequence by using the hidden Markov Model (HMM). In this PhD, we describe a new structural alphabet, improving the existing HMM-SA27 structural alphabet, called SAFlex (Structural Alphabet Flexibility), in order to take into account the uncertainty of data (missing data in PDB files) and the redundancy of protein structures. The new SAFlex structural alphabet obtained therefore offers a new, rigorous and robust encoding model. This encoding takes into account the encoding uncertainty by providing three encoding options: the maximum a posteriori (MAP), the marginal posterior distribution (POST), and the effective number of letters at each given position (NEFF). SAFlex also provides and builds a consensus encoding from different replicates (multiple chains, monomers and several homomers) of a single protein. It thus allows the detection of structural variability between different chains. The methodological advances and the achievement of the SAFlex alphabet are the main contributions of this PhD. We also present the new PDB parser(SAFlex-PDB) and we demonstrate that our parser is therefore interesting both qualitative (detection of various errors) and quantitative terms (program optimization and parallelization) by comparing it with two other parsers well-known in the area of Bioinformatics (Biopython and BioJava). The SAFlex structural alphabet is being made available to the scientific community by providing a website. The SAFlex web server represents the concrete contribution of this PhD while the SAFlex-PDB parser represents an important contribution to the proper function of the proposed website. Here, we describe the functions and the interfaces of the SAFlex web server. The SAFlex can be used in various fashions for a protein tertiary structure of a given PDB format file; it can be used for encoding the 3D structure, identifying and predicting missing data. Hence, it is the only alphabet able to encode and predict the missing data in a 3D protein structure to date. Finally, these improvements; are promising to explore increasing protein redundancy data and obtain useful quantification of their flexibility
Landelle, Benoit. "Étude Statistique du Problème de la Trajectographie Passive". Phd thesis, Université Paris Sud - Paris XI, 2009. http://tel.archives-ouvertes.fr/tel-00386071.
Pełny tekst źródłaMirauta, Bogdan. "Etude du transcriptome à partir de données de comptages issues de séquençage haut débit". Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066424.
Pełny tekst źródłaIn this thesis we address the problem of reconstructing the transcription profile from RNA-Seq reads in cases where the reference genome is available but without making use of existing annotation. In the first two chapters consist of an introduction to the biological context, high-throughput sequencing and the statistical methods that can be used in the analysis of series of counts. Then we present our contribution for the RNA-Seq read count model, the inference transcription profile by using Particle Gibbs and the reconstruction of DE regions. The analysis of several data-sets proved that using Negative Binomial distributions to model the read count emission is not generally valid. We develop a mechanistic model which accounts for the randomness generated within all RNA-Seq protocol steps. Such a model is particularly important for the assessment of the credibility intervals associated with the transcription level and coverage changes. Next, we describe a State Space Model accounting for the read count profile for observations and transcription profile for the latent variable. For the transition kernel we design a mixture model combining the possibility of making, between two adjacent positions, no move, a drift move or a shift move. We detail our approach for the reconstruction of the transcription profile and the estimation of parameters using the Particle Gibbs algorithm. In the fifth chapter we complete the results by presenting an approach for analysing differences in expression without making use of existing annotation. The proposed method first approximates these differences for each base-pair and then aggregates continuous DE regions
Mirauta, Bogdan. "Etude du transcriptome à partir de données de comptages issues de séquençage haut débit". Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066424/document.
Pełny tekst źródłaIn this thesis we address the problem of reconstructing the transcription profile from RNA-Seq reads in cases where the reference genome is available but without making use of existing annotation. In the first two chapters consist of an introduction to the biological context, high-throughput sequencing and the statistical methods that can be used in the analysis of series of counts. Then we present our contribution for the RNA-Seq read count model, the inference transcription profile by using Particle Gibbs and the reconstruction of DE regions. The analysis of several data-sets proved that using Negative Binomial distributions to model the read count emission is not generally valid. We develop a mechanistic model which accounts for the randomness generated within all RNA-Seq protocol steps. Such a model is particularly important for the assessment of the credibility intervals associated with the transcription level and coverage changes. Next, we describe a State Space Model accounting for the read count profile for observations and transcription profile for the latent variable. For the transition kernel we design a mixture model combining the possibility of making, between two adjacent positions, no move, a drift move or a shift move. We detail our approach for the reconstruction of the transcription profile and the estimation of parameters using the Particle Gibbs algorithm. In the fifth chapter we complete the results by presenting an approach for analysing differences in expression without making use of existing annotation. The proposed method first approximates these differences for each base-pair and then aggregates continuous DE regions
Le, Barz Cédric. "Navigation visuelle pour les missions autonomes des petits drones". Thesis, Paris 6, 2015. http://www.theses.fr/2015PA066424/document.
Pełny tekst źródłaIn this last decade, technology evolution has enabled the development of small and light UAV able to evolve in indoor and urban environments. In order to execute missions assigned to them, UAV must have a robust navigation system, including a precise egolocalization functionality within an absolute reference. We propose to solve this problem by mapping the latest images acquired with geo-referenced images, i.e. Google Streetview images.In a first step, assuming that it is possible for a given query image to retrieve the geo-referenced image depicting the same scene, we study a solution, based on relative pose estimation between images, to refine the location. Then, to retrieve geo-referenced images corresponding to acquired images, we studied and proposed an hybrid method exploiting both visual and odometric information by defining an appropriate Hidden Markov Model (HMM), where states are geographical locations. The quality of achieved performances depending of visual similarities, we finally proposed an original solution based on a supervised metric learning solution. The solution measures similarities between the query images and geo-referenced images close to the putative position, thanks to distances learnt during a preliminary step
Le, Barz Cédric. "Navigation visuelle pour les missions autonomes des petits drones". Electronic Thesis or Diss., Paris 6, 2015. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2015PA066424.pdf.
Pełny tekst źródłaIn this last decade, technology evolution has enabled the development of small and light UAV able to evolve in indoor and urban environments. In order to execute missions assigned to them, UAV must have a robust navigation system, including a precise egolocalization functionality within an absolute reference. We propose to solve this problem by mapping the latest images acquired with geo-referenced images, i.e. Google Streetview images.In a first step, assuming that it is possible for a given query image to retrieve the geo-referenced image depicting the same scene, we study a solution, based on relative pose estimation between images, to refine the location. Then, to retrieve geo-referenced images corresponding to acquired images, we studied and proposed an hybrid method exploiting both visual and odometric information by defining an appropriate Hidden Markov Model (HMM), where states are geographical locations. The quality of achieved performances depending of visual similarities, we finally proposed an original solution based on a supervised metric learning solution. The solution measures similarities between the query images and geo-referenced images close to the putative position, thanks to distances learnt during a preliminary step
Chopin, Nicolas. "Applications des méthodes de Monte Carlo séquentielles à la statistique bayésienne". Paris 6, 2003. http://www.theses.fr/2003PA066057.
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