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Rozprawy doktorskie na temat „Gaussian mixture models”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 25 lipca 2025

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1

Kunkel, Deborah Elizabeth. "Anchored Bayesian Gaussian Mixture Models." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1524134234501475.

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Nkadimeng, Calvin. "Language identification using Gaussian mixture models." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4170.

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Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2010.<br>ENGLISH ABSTRACT: The importance of Language Identification for African languages is seeing a dramatic increase due to the development of telecommunication infrastructure and, as a result, an increase in volumes of data and speech traffic in public networks. By automatically processing the raw speech data the vital assistance given to people in distress can be speeded up, by referring their calls to a person knowledgeable in that language. To this effect a speech corpus was developed and various

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Gundersen, Terje. "Voice Transformation based on Gaussian mixture models." Thesis, Norwegian University of Science and Technology, Department of Electronics and Telecommunications, 2010. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10878.

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<p>In this thesis, a probabilistic model for transforming a voice to sound like another specific voice is tested. The model is fully automatic and only requires some 100 training sentences from both speakers with the same acoustic content. The classical source-filter decomposition allows prosodic and spectral transformation to be performed independently. The transformations are based on a Gaussian mixture model and a transformation function suggested by Y. Stylianou. Feature vectors of the same content from the source and target speaker, aligned in time by dynamic time warping, are fitted to a

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Subramaniam, Anand D. "Gaussian mixture models in compression and communication /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2003. http://wwwlib.umi.com/cr/ucsd/fullcit?p3112847.

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Cilliers, Francois Dirk. "Tree-based Gaussian mixture models for speaker verification." Thesis, Link to the online version, 2005. http://hdl.handle.net/10019.1/1639.

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Lu, Liang. "Subspace Gaussian mixture models for automatic speech recognition." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8065.

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In most of state-of-the-art speech recognition systems, Gaussian mixture models (GMMs) are used to model the density of the emitting states in the hidden Markov models (HMMs). In a conventional system, the model parameters of each GMM are estimated directly and independently given the alignment. This results a large number of model parameters to be estimated, and consequently, a large amount of training data is required to fit the model. In addition, different sources of acoustic variability that impact the accuracy of a recogniser such as pronunciation variation, accent, speaker factor and en

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Pinto, Rafael Coimbra. "Continuous reinforcement learning with incremental Gaussian mixture models." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/157591.

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A contribução original desta tese é um novo algoritmo que integra um aproximador de funções com alta eficiência amostral com aprendizagem por reforço em espaços de estados contínuos. A pesquisa completa inclui o desenvolvimento de um algoritmo online e incremental capaz de aprender por meio de uma única passada sobre os dados. Este algoritmo, chamado de Fast Incremental Gaussian Mixture Network (FIGMN) foi empregado como um aproximador de funções eficiente para o espaço de estados de tarefas contínuas de aprendizagem por reforço, que, combinado com Q-learning linear, resulta em performance com

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Chockalingam, Prakash. "Non-rigid multi-modal object tracking using Gaussian mixture models." Connect to this title online, 2009. http://etd.lib.clemson.edu/documents/1252937467/.

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Thesis (M.S.) -- Clemson University, 2009.<br>Contains additional supplemental files. Title from first page of PDF file. Document formatted into pages; contains vii, 54 p. ; also includes color graphics.

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9

Wang, Bo Yu. "Deterministic annealing EM algorithm for robust learning of Gaussian mixture models." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2493309.

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Plasse, Joshua H. "The EM Algorithm in Multivariate Gaussian Mixture Models using Anderson Acceleration." Digital WPI, 2013. https://digitalcommons.wpi.edu/etd-theses/290.

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Over the years analysts have used the EM algorithm to obtain maximum likelihood estimates from incomplete data for various models. The general algorithm admits several appealing properties such as strong global convergence; however, the rate of convergence is linear which in some cases may be unacceptably slow. This work is primarily concerned with applying Anderson acceleration to the EM algorithm for Gaussian mixture models (GMM) in hopes of alleviating slow convergence. As preamble we provide a review of maximum likelihood estimation and derive the EM algorithm in detail. The iterates that

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MENDES, EDUARDO FONSECA. "MODELING NONLINEAR TIME SERIES WITH A TREE-STRUCTURED MIXTURE OF GAUSSIAN MODELS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9689@1.

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COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>Neste trabalho um novo modelo de mistura de distribuições é proposto, onde a estrutura da mistura é determinada por uma árvore de decisão com transição suave. Modelos baseados em mistura de distribuições são úteis para aproximar distribuições condicionais desconhecidas de dados multivariados. A estrutura em árvore leva a um modelo que é mais simples, e em alguns casos mais interpretável, do que os propostos anteriormente na literatura. Baseando-se no algoritmo de Esperança- Maximização (EM), foi derivado um estimador de qu

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12

Sondergaard, Thomas S. M. Massachusetts Institute of Technology. "Data assimilation with Gaussian mixture models using the dynamically orthogonal field equations." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/68954.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2011.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 177-180).<br>Data assimilation, as presented in this thesis, is the statistical merging of sparse observational data with computational models so as to optimally improve the probabilistic description of the field of interest, thereby reducing uncertainties. The centerpiece of this thesis is the introduction of a novel such scheme that overcomes prior shortcomings observed within the community. Adopting techniques preval

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Stewart, Michael Ian. "Asymptotic methods for tests of homogeneity for finite mixture models." Thesis, The University of Sydney, 2002. http://hdl.handle.net/2123/855.

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We present limit theory for tests of homogeneity for finite mixture models. More specifically, we derive the asymptotic distribution of certain random quantities used for testing that a mixture of two distributions is in fact just a single distribution. Our methods apply to cases where the mixture component distributions come from one of a wide class of one-parameter exponential families, both continous and discrete. We consider two random quantities, one related to testing simple hypotheses, the other composite hypotheses. For simple hypotheses we consider the maximum of the standard

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Stewart, Michael Ian. "Asymptotic methods for tests of homogeneity for finite mixture models." University of Sydney. Mathematics and Statistics, 2002. http://hdl.handle.net/2123/855.

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We present limit theory for tests of homogeneity for finite mixture models. More specifically, we derive the asymptotic distribution of certain random quantities used for testing that a mixture of two distributions is in fact just a single distribution. Our methods apply to cases where the mixture component distributions come from one of a wide class of one-parameter exponential families, both continous and discrete. We consider two random quantities, one related to testing simple hypotheses, the other composite hypotheses. For simple hypotheses we consider the maximum of the standard

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Diaz, Jorge Cristhian Chamby. "An incremental gaussian mixture network for data stream classification in non-stationary environments." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/174484.

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Classificação de fluxos contínuos de dados possui muitos desafios para a comunidade de mineração de dados quando o ambiente não é estacionário. Um dos maiores desafios para a aprendizagem em fluxos contínuos de dados está relacionado com a adaptação às mudanças de conceito, as quais ocorrem como resultado da evolução dos dados ao longo do tempo. Duas formas principais de desenvolver abordagens adaptativas são os métodos baseados em conjunto de classificadores e os algoritmos incrementais. Métodos baseados em conjunto de classificadores desempenham um papel importante devido à sua modularidade,

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Stewart, Michael. "Asymptotic methods for tests of homogeneity for finite mixture models." Connect to full text, 2002. http://hdl.handle.net/2123/855.

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Thesis (Ph. D.)--University of Sydney, 2002.<br>Title from title screen (viewed Apr. 28, 2008). Submitted in fulfilment of the requirements for the degree of Doctor of Philosophy to the School of Mathematics and Statistics, Faculty of Science. Includes bibliography. Also available in print form.

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Fernandes, maligo Artur otavio. "Unsupervised Gaussian mixture models for the classification of outdoor environments using 3D terrestrial lidar data." Thesis, Toulouse, INSA, 2016. http://www.theses.fr/2016ISAT0053/document.

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Le traitement de nuages de points 3D de lidars permet aux robots mobiles autonomes terrestres de construire des modèles sémantiques de l'environnement extérieur dans lequel ils évoluent. Ces modèles sont intéressants car ils représentent des informations qualitatives, et ainsi donnent à un robot la capacité de raisonner à un niveau plus élevé d'abstraction. Le coeur d'un système de modélisation sémantique est la capacité de classifier les observations venant du capteur. Nous proposons un système de classification centré sur l'apprentissage non-supervisé. La prémière couche, la couche intermédi

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Tomashenko, Natalia. "Speaker adaptation of deep neural network acoustic models using Gaussian mixture model framework in automatic speech recognition systems." Thesis, Le Mans, 2017. http://www.theses.fr/2017LEMA1040/document.

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Les différences entre conditions d'apprentissage et conditions de test peuvent considérablement dégrader la qualité des transcriptions produites par un système de reconnaissance automatique de la parole (RAP). L'adaptation est un moyen efficace pour réduire l'inadéquation entre les modèles du système et les données liées à un locuteur ou un canal acoustique particulier. Il existe deux types dominants de modèles acoustiques utilisés en RAP : les modèles de mélanges gaussiens (GMM) et les réseaux de neurones profonds (DNN). L'approche par modèles de Markov cachés (HMM) combinés à des GMM (GMM-HM

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Safont, Armero Gonzalo. "New Insights in Prediction and Dynamic Modeling from Non-Gaussian Mixture Processing Methods." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/53913.

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[EN] This thesis considers new applications of non-Gaussian mixtures in the framework of statistical signal processing and pattern recognition. The non-Gaussian mixtures were implemented by mixtures of independent component analyzers (ICA). The fundamental hypothesis of ICA is that the observed signals can be expressed as a linear transformation of a set of hidden variables, usually referred to as sources, which are statistically independent. This independence allows factoring the original M-dimensional probability density function (PDF) of the data as a product of one-dimensional probability

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Abbi, Revlin. "A Paitent Length of Stay Grouping and Predicting methodology incorporating Gaussian mixture Models and Classification Algorithms." Thesis, University of Westminster, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.500554.

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Avila, Anderson Raymundo. "A comparative analysis of gaussian mixture models and i-vector for speaker verification under mismatched conditions." reponame:Repositório Institucional da UFABC, 2014.

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Orientador: Prof. Dr. Francisco J. Fraga<br>Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, 2014.<br>Most speaker verifcation systems are based on Gaussian mixture models and more recently on the so-called i-vector. These two methods are affected in mismatched testtrain conditions, which might be caused by vocal-efort variability, different speakingstyles or channel efects. In this work, we compared the impact of speech rate variation and room reverberation on both methods. We found that performance degradation due to variation on sp

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Webb, Grayson. "A Gaussian Mixture Model based Level Set Method for Volume Segmentation in Medical Images." Thesis, Linköpings universitet, Beräkningsmatematik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148548.

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This thesis proposes a probabilistic level set method to be used in segmentation of tumors with heterogeneous intensities. It models the intensities of the tumor and surrounding tissue using Gaussian mixture models. Through a contour based initialization procedure samples are gathered to be used in expectation maximization of the mixture model parameters. The proposed method is compared against a threshold-based segmentation method using MRI images retrieved from The Cancer Imaging Archive. The cases are manually segmented and an automated testing procedure is used to find optimal parameters f

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Kaba, Djibril. "Computational models for stuctural analysis of retinal images." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/10387.

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The evaluation of retina structures has been of great interest because it could be used as a non-intrusive diagnosis in modern ophthalmology to detect many important eye diseases as well as cardiovascular disorders. A variety of retinal image analysis tools have been developed to assist ophthalmologists and eye diseases experts by reducing the time required in eye screening, optimising the costs as well as providing efficient disease treatment and management systems. A key component in these tools is the segmentation and quantification of retina structures. However, the imaging artefacts such

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Zhou, Linfei [Verfasser], and Christian [Akademischer Betreuer] Böhm. "Indexing and knowledge discovery of gaussian mixture models and multiple-instance learning / Linfei Zhou ; Betreuer: Christian Böhm." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2018. http://d-nb.info/1152210807/34.

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Kullmann, Emelie. "Speech to Text for Swedish using KALDI." Thesis, KTH, Optimeringslära och systemteori, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189890.

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The field of speech recognition has during the last decade left the re- search stage and found its way in to the public market. Most computers and mobile phones sold today support dictation and transcription in a number of chosen languages. Swedish is often not one of them. In this thesis, which is executed on behalf of the Swedish Radio, an Automatic Speech Recognition model for Swedish is trained and the performance evaluated. The model is built using the open source toolkit Kaldi. Two approaches of training the acoustic part of the model is investigated. Firstly, using Hidden Markov Model

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Van, Eeden Willem Daniel. "Human and animal classification using Doppler radar." Diss., University of Pretoria, 2005. http://hdl.handle.net/2263/66252.

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South Africa is currently struggling to deal with a significant poaching and livestock theft problem. This work is concerned with the detection and classification of ground based targets using radar micro- Doppler signatures to aid in the monitoring of borders, nature reserves and farmlands. The research starts of by investigating the state of the art of ground target classification. Different radar systems are investigated with respect to their ability to classify targets at different operating frequencies. Finally, a Gaussian Mixture Model Hidden Markov Model based (GMM-HMM) classification a

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Nikša, Jakovljević. "Primena retke reprezentacije na modelima Gausovih mešavina koji se koriste za automatsko prepoznavanje govora." Phd thesis, Univerzitet u Novom Sadu, Fakultet tehničkih nauka u Novom Sadu, 2014. http://dx.doi.org/10.2298/NS20131218JAKOVLJEVIC.

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U ovoj disertaciji je predstavljen model koji aproksimira pune kova-rijansne matrice u modelu gausovih mešavina (GMM) sa smanjenimbrojem parametara i izračunavanja koji su potrebni za izračunavanjeizglednosti. U predloženom modelu inverzne kovarijansne matrice suaproksimirane korišćenjem retke reprezentacije njihovih karakteri-stičnih vektora. Pored samog modela prikazan je i algoritam zaestimaciju parametara zasnovan na kriterijumu maksimizacijeizgeldnosti. Eksperimentalni rezultati na problemu prepoznavanjagovora su pokazali da predloženi model za isti nivo greške kao GMMsa upunim kovarijans

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Wood, John. "Statistical Background Models with Shadow Detection for Video Based Tracking." Thesis, Linköping University, Department of Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8667.

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<p>A common problem when using background models to segment moving objects from video sequences is that objects cast shadow usually significantly differ from the background and therefore get detected as foreground. This causes several problems when extracting and labeling objects, such as object shape distortion and several objects merging together. The purpose of this thesis is to explore various possibilities to handle this problem.</p><p>Three methods for statistical background modeling are reviewed. All methods work on a per pixel basis, the first is based on approximating the median, the

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Liu, Peng. "Adaptive Mixture Estimation and Subsampling PCA." Case Western Reserve University School of Graduate Studies / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1220644686.

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Madsen, Christopher. "Clustering of the Stockholm County housing market." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252301.

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In this thesis a clustering of the Stockholm county housing market has been performed using different clustering methods. Data has been derived and different geographical constraints have been used. DeSO areas (Demographic statistical areas), developed by SCB, have been used to divide the housing market in to smaller regions for which the derived variables have been calculated. Hierarchical clustering methods, SKATER and Gaussian mixture models have been applied. Methods using different kinds of geographical constraints have also been applied in an attempt to create more geographically contigu

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DApuzzo, Daniele. "It Is Better to Be Upside Than Sharpe!" BYU ScholarsArchive, 2017. https://scholarsarchive.byu.edu/etd/6705.

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Based on the assumption that returns in Commercial Real Estate are normally distributed, the Sharpe Ratio has been the standard risk-adjusted performance measure for the past several years. Research has questioned whether this assumption can be reasonably made. The Upside Potential Ratio as a risk-adjusted performance measure is an alternative to measure performance on a risk-adjusted basis but its values differ from the Sharpe Ratio's only in the assumption of skewed returns. We will provide reasonable evidence that CRE returns should not be fitted with a normal distribution and present the G

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Chassagnol, Bastien. "Application of Multivariate Gaussian Convolution and Mixture Models for Identifying Key Biomarkers Underlying Variability in Transcriptomic Profiles and the Diversity of Therapeutic Responses." Electronic Thesis or Diss., Sorbonne université, 2023. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2023SORUS512.pdf.

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La diversité des phénotypes et des conditions observées au sein de l'espèce humaine est le résultat de multiples processus biologiques interdépendants. Cependant, dans le contexte de la médecine personnalisée et du traitement de maladies de plus en plus complexes, systématiques et hétérogènes, il est crucial de développer des approches qui capturent de manière exhaustive la complexité des mécanismes biologiques sous-jacents à la variabilité des profils biologiques. Cela s'étend du niveau individuel au niveau cellulaire, englobant les tissus et les organes. Une telle précision et une telle gran

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Idvall, Patrik, and Conny Jonsson. "Algorithmic Trading : Hidden Markov Models on Foreign Exchange Data." Thesis, Linköping University, Department of Mathematics, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10719.

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<p>In this master's thesis, hidden Markov models (HMM) are evaluated as a tool for forecasting movements in a currency cross. With an ever increasing electronic market, making way for more automated trading, or so called algorithmic trading, there is constantly a need for new trading strategies trying to find alpha, the excess return, in the market.</p><p>HMMs are based on the well-known theories of Markov chains, but where the states are assumed hidden, governing some observable output. HMMs have mainly been used for speech recognition and communication systems, but have lately also been util

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Sehili, Mohamed el Amine. "Reconnaissance des sons de l’environnement dans un contexte domotique." Thesis, Evry, Institut national des télécommunications, 2013. http://www.theses.fr/2013TELE0014/document.

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Dans beaucoup de pays du monde, on observe une importante augmentation du nombre de personnes âgées vivant seules. Depuis quelques années, un nombre significatif de projets de recherche sur l’assistance aux personnes âgées ont vu le jour. La plupart de ces projets utilisent plusieurs modalités (vidéo, son, détection de chute, etc.) pour surveiller l'activité de la personne et lui permettre de communiquer naturellement avec sa maison "intelligente", et, en cas de danger, lui venir en aide au plus vite. Ce travail a été réalisé dans le cadre du projet ANR VERSO de recherche industrielle, Sweet-H

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Hansson, Agnes. "Understanding people movement and detecting anomalies using probabilistic generative models." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-288496.

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As intelligent access solutions begin to dominate the world, the statistical learning methods to answer for the behavior of these needs attention, as there is no clear answer to how an algorithm could learn and predict exactly how people move. This project aims at investigating if, with the help of unsupervised learning methods, it is possible to distinguish anomalies from normal events in an access system, and if the most probable choice of cylinder to be unlocked by a user can be calculated.Given to do this is a data set of the previous events in an access system, together with the access co

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Torres, Lianet Sepúlveda. "Representações hierárquicas de vocábulos de línguas indígenas brasileiras: modelos baseados em mistura de Gaussianas." Universidade de São Paulo, 2010. http://www.teses.usp.br/teses/disponiveis/18/18152/tde-22122010-154505/.

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Apesar da ampla diversidade de línguas indígenas no Brasil, poucas pesquisas estudam estas línguas e suas relações. Inúmeros esforços têm sido dedicados a procurar similaridades entre as palavras das línguas indígenas e classificá-las em famílias de línguas. Seguindo a classificação mais aceita das línguas indígenas do Brasil, esta pesquisa propõe comparar palavras de 10 línguas indígenas brasileiras. Para isso, considera-se que estas palavras são sinais de fala e estima-se a função de distribuição de probabilidade (PDF) de cada palavra, usando um modelo de mistura de gaussianas (GMM). A PDF f

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Westerlund, Annie M. "Computational Study of Calmodulin’s Ca2+-dependent Conformational Ensembles." Licentiate thesis, KTH, Biofysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-234888.

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Ca2+ and calmodulin play important roles in many physiologically crucial pathways. The conformational landscape of calmodulin is intriguing. Conformational changes allow for binding target-proteins, while binding Ca2+ yields population shifts within the landscape. Thus, target-proteins become Ca2+-sensitive upon calmodulin binding. Calmodulin regulates more than 300 target-proteins, and mutations are linked to lethal disorders. The mechanisms underlying Ca2+ and target-protein binding are complex and pose interesting questions. Such questions are typically addressed with experiments which fail

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Dahl, Oskar, and Fredrik Johansson. "Understanding usage of Volvo trucks." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-40826.

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Trucks are designed, configured and marketed for various working environments. There lies a concern whether trucks are used as intended by the manufacturer, as usage may impact the longevity, efficiency and productivity of the trucks. In this thesis we propose a framework divided into two separate parts, that aims to extract costumers’ driving behaviours from Logged Vehicle Data (LVD) in order to a): evaluate whether they align with so-called Global Transport Application (GTA) parameters and b): evaluate the usage in terms of performance. Gaussian mixture model (GMM) is employed to cluster and

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McLaren, Mitchell Leigh. "Improving automatic speaker verification using SVM techniques." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/32063/1/Mitchell_McLaren_Thesis.pdf.

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Automatic recognition of people is an active field of research with important forensic and security applications. In these applications, it is not always possible for the subject to be in close proximity to the system. Voice represents a human behavioural trait which can be used to recognise people in such situations. Automatic Speaker Verification (ASV) is the process of verifying a persons identity through the analysis of their speech and enables recognition of a subject at a distance over a telephone channel { wired or wireless. A significant amount of research has focussed on the applicati

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Ruan, Lingyan. "Statistical analysis of high dimensional data." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37135.

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This century is surely the century of data (Donoho, 2000). Data analysis has been an emerging activity over the last few decades. High dimensional data is in particular more and more pervasive with the advance of massive data collection system, such as microarrays, satellite imagery, and financial data. However, analysis of high dimensional data is of challenge with the so called curse of dimensionality (Bellman 1961). This research dissertation presents several methodologies in the application of high dimensional data analysis. The first part discusses a joint analysis of multiple microarray

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Molin, Joel. "Foreground Segmentation of Moving Objects." Thesis, Linköping University, Department of Electrical Engineering, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52544.

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<p>Foreground segmentation is a common first step in tracking and surveillance applications. The purpose of foreground segmentation is to provide later stages of image processing with an indication of where interesting data can be found. This thesis is an investigation of how foreground segmentation can be performed in two contexts: as a pre-step to trajectory tracking and as a pre-step in indoor surveillance applications.</p><p>Three methods are selected and detailed: a single Gaussian method, a Gaussian mixture model method, and a codebook method. Experiments are then performed on typical

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AlMutairi, Bandar Saud. "Statistical Models for Characterizing and Reducing Uncertainty in Seasonal Rainfall Pattern Forecasts to Inform Decision Making." Research Showcase @ CMU, 2017. http://repository.cmu.edu/dissertations/940.

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Uncertainty in rainfall forecasts affects the level of quality and assurance for decisions made to manage water resource-based systems. However, eliminating uncertainty in a complete manner could be difficult, decision-makers thus are challenged to make decisions in the light of uncertainty. This study provides statistical models as an approach to cope with uncertainty, including: a) a statistical method relying on a Gaussian mixture (GM) model to assist in better characterize uncertainty in climate model projections and evaluate their performance in matching observations; b) a stochastic mode

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Carvalho, Edigleison Francelino. "Probabilistic incremental learning for image recognition : modelling the density of high-dimensional data." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2014. http://hdl.handle.net/10183/90429.

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Atualmente diversos sistemas sensoriais fornecem dados em fluxos e essas observações medidas são frequentemente de alta dimensionalidade, ou seja, o número de variáveis medidas é grande, e as observações chegam em sequência. Este é, em particular, o caso de sistemas de visão em robôs. Aprendizagem supervisionada e não-supervisionada com esses fluxos de dados é um desafio, porque o algoritmo deve ser capaz de aprender com cada observação e depois descartá-la antes de considerar a próxima, mas diversos métodos requerem todo o conjunto de dados a fim de estimar seus parâmetros e, portanto, não sã

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Fossà, Alberto. "Propagation multi-fidélité d’incertitude orbitale en présence d’accélérations stochastiques." Electronic Thesis or Diss., Toulouse, ISAE, 2024. http://www.theses.fr/2024ESAE0009.

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Le problème de la propagation non linéaire d’incertitude est crucial en astrodynamique, car tous les systèmes d’intérêt pratique, allant de la navigation à la détermination d’orbite et au suivi de cibles, impliquent des non-linéarités dans leurs modèles dynamiques et de mesure. Un sujet d’intérêt est la propagation précise d’incertitude à travers la dynamique orbitale non linéaire, une exigence fondamentale dans plusieurs applications telles que la surveillance de l’espace, la gestion du trafic spatial et la fin de vie des satellites. Étant donnée une représentation dimensionnelle finie de la

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Fang, Zaili. "Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/40090.

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Model and variable selection have attracted considerable attention in areas of application where datasets usually contain thousands of variables. Variable selection is a critical step to reduce the dimension of high dimensional data by eliminating irrelevant variables. The general objective of variable selection is not only to obtain a set of cost-effective predictors selected but also to improve prediction and prediction variance. We have made several contributions to this issue through a range of advanced topics: providing a graphical view of Bayesian Variable Selection (BVS), recovering s

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Wu, Jingwen. "Model-based clustering and model selection for binned data." Thesis, Supélec, 2014. http://www.theses.fr/2014SUPL0005/document.

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Cette thèse étudie les approches de classification automatique basées sur les modèles de mélange gaussiens et les critères de choix de modèles pour la classification automatique de données discrétisées. Quatorze algorithmes binned-EM et quatorze algorithmes bin-EM-CEM sont développés pour quatorze modèles de mélange gaussiens parcimonieux. Ces nouveaux algorithmes combinent les avantages des données discrétisées en termes de réduction du temps d’exécution et les avantages des modèles de mélange gaussiens parcimonieux en termes de simplification de l'estimation des paramètres. Les complexités d

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Akhtar, Mahmood Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Genomic sequence processing: gene finding in eukaryotes." Publisher:University of New South Wales. Electrical Engineering & Telecommunications, 2008. http://handle.unsw.edu.au/1959.4/40912.

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Of the many existing eukaryotic gene finding software programs, none are able to guarantee accurate identification of genomic protein coding regions and other biological signals central to pathway from DNA to the protein. Eukaryotic gene finding is difficult mainly due to noncontiguous and non-continuous nature of genes. Existing approaches are heavily dependent on the compositional statistics of the sequences they learn from and are not equally suitable for all types of sequences. This thesis firstly develops efficient digital signal processing-based methods for the identification of genomic

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Swathanthira, Kumar Murali Murugavel M. "Magnetic Resonance Image segmentation using Pulse Coupled Neural Networks." Digital WPI, 2009. https://digitalcommons.wpi.edu/etd-dissertations/280.

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The Pulse Couple Neural Network (PCNN) was developed by Eckhorn to model the observed synchronization of neural assemblies in the visual cortex of small mammals such as a cat. In this dissertation, three novel PCNN based automatic segmentation algorithms were developed to segment Magnetic Resonance Imaging (MRI) data: (a) PCNN image 'signature' based single region cropping; (b) PCNN - Kittler Illingworth minimum error thresholding and (c) PCNN -Gaussian Mixture Model - Expectation Maximization (GMM-EM) based multiple material segmentation. Among other control tests, the proposed algorithms wer

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Gurrapu, Chaitanya. "Human Action Recognition In Video Data For Surveillance Applications." Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/15878/1/Chaitanya_Gurrapu_Thesis.pdf.

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Detecting human actions using a camera has many possible applications in the security industry. When a human performs an action, his/her body goes through a signature sequence of poses. To detect these pose changes and hence the activities performed, a pattern recogniser needs to be built into the video system. Due to the temporal nature of the patterns, Hidden Markov Models (HMM), used extensively in speech recognition, were investigated. Initially a gesture recognition system was built using novel features. These features were obtained by approximating the contour of the foreground object wi

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Gurrapu, Chaitanya. "Human Action Recognition In Video Data For Surveillance Applications." Queensland University of Technology, 2004. http://eprints.qut.edu.au/15878/.

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Detecting human actions using a camera has many possible applications in the security industry. When a human performs an action, his/her body goes through a signature sequence of poses. To detect these pose changes and hence the activities performed, a pattern recogniser needs to be built into the video system. Due to the temporal nature of the patterns, Hidden Markov Models (HMM), used extensively in speech recognition, were investigated. Initially a gesture recognition system was built using novel features. These features were obtained by approximating the contour of the foreground object wi

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