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Tesi sul tema "Hiden Markov model"

Autore: Grafiati

Pubblicato: 1 luglio 2022

Ultima modifica: 19 luglio 2025

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1

Devilliers, Esther. "Modélisation micro-économétrique des choix de pratiques de production et des utilisations d'intrants chimiques des agriculteurs : une approche par les fonctions de production latentes." Thesis, Rennes, Agrocampus Ouest, 2021. http://www.theses.fr/2021NSARE058.

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La notion d’itinéraire technique est une notion agronomique qui nous permet d’appréhender l’imbrication entre les rendements objectifs et les niveaux d’utilisation d’intrants associés. Dès lors, on peut admettre qu’à différents types d’itinéraires techniques correspondent différentes fonctions de production. Modéliser ces différentes fonctions est une des clés pour mieux comprendre la dépendance de certaines pratiques culturales aux pesticides et de ce fait constitue un enjeu majeur pour concevoir les futures politiques publiques.Intégrer cette notion d’itinéraire technique nécessite de tenir

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2

Kotsalis, Georgios. "Model reduction for Hidden Markov models." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38255.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.<br>Includes bibliographical references (leaves 57-60).<br>The contribution of this thesis is the development of tractable computational methods for reducing the complexity of two classes of dynamical systems, finite alphabet Hidden Markov Models and Jump Linear Systems with finite parameter space. The reduction algorithms employ convex optimization and numerical linear algebra tools and do not pose any structural requirements on the systems at hand. In the Jump Linear Systems case, a distance metric

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3

Kadhem, Safaa K. "Model fit diagnostics for hidden Markov models." Thesis, University of Plymouth, 2017. http://hdl.handle.net/10026.1/9966.

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Hidden Markov models (HMMs) are an efficient tool to describe and model the underlying behaviour of many phenomena. HMMs assume that the observed data are generated independently from a parametric distribution, conditional on an unobserved process that satisfies the Markov property. The model selection or determining the number of hidden states for these models is an important issue which represents the main interest of this thesis. Applying likelihood-based criteria for HMMs is a challenging task as the likelihood function of these models is not available in a closed form. Using the data augm

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4

Bulla, Jan. "Application of Hidden Markov and Hidden Semi-Markov Models to Financial Time Series." Doctoral thesis, [S.l. : s.n.], 2006. http://swbplus.bsz-bw.de/bsz260867136inh.pdf.

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5

Wynne-Jones, Michael. "Model building in neural networks with hidden Markov models." Thesis, University of Edinburgh, 1994. http://hdl.handle.net/1842/284.

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This thesis concerns the automatic generation of architectures for neural networks and other pattern recognition models comprising many elements of the same type. The requirement for such models, with automatically determined topology and connectivity, arises from two needs. The first is the need to develop commercial applications of the technology without resorting to laborious trial and error with different network sizes; the second is the need, in large and complex pattern processing applications such as speech recognition, to optimise the allocation of computing resources for problem solvi

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6

Tillman, Måns. "On-Line Market Microstructure Prediction Using Hidden Markov Models." Thesis, KTH, Matematisk statistik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208312.

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Over the last decades, financial markets have undergone dramatic changes. With the advent of the arbitrage pricing theory, along with new technology, markets have become more efficient. In particular, the new high-frequency markets, with algorithmic trading operating on micro-second level, make it possible to translate ”information” into price almost instantaneously. Such phenomena are studied in the field of market microstructure theory, which aims to explain and predict them. In this thesis, we model the dynamics of high frequency markets using non-linear hidden Markov models (HMMs). Such mo

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7

Hofer, Gregor Otto. "Speech-driven animation using multi-modal hidden Markov models." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/3786.

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The main objective of this thesis was the synthesis of speech synchronised motion, in particular head motion. The hypothesis that head motion can be estimated from the speech signal was confirmed. In order to achieve satisfactory results, a motion capture data base was recorded, a definition of head motion in terms of articulation was discovered, a continuous stream mapping procedure was developed, and finally the synthesis was evaluated. Based on previous research into non-verbal behaviour basic types of head motion were invented that could function as modelling units. The stream mapping meth

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8

McKee, Bill Frederick. "Optimal hidden Markov models." Thesis, University of Plymouth, 1999. http://hdl.handle.net/10026.1/1698.

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In contrast with training algorithms such as Baum-Welch, which produce solutions that are a local optimum of the objective function, this thesis describes the attempt to develop a training algorithm which delivers the global optimum Discrete ICdden Markov Model for a given training sequence. A total of four different methods of attack upon the problem are presented. First, after building the necessary analytical tools, the thesis presents a direct, calculus-based assault featuring Matrix Derivatives. Next, the dual analytic approach known as Geometric Programming is examined and then adapted t

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9

Schimert, James. "A high order hidden Markov model /." Thesis, Connect to this title online; UW restricted, 1992. http://hdl.handle.net/1773/8939.

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10

Chong, Fong Ho. "Frequency-stream-tying hidden Markov model /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202003%20CHONG.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2003.<br>Includes bibliographical references (leaves 119-123). Also available in electronic version. Access restricted to campus users.

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11

Kato, Akihiro. "Hidden Markov model-based speech enhancement." Thesis, University of East Anglia, 2017. https://ueaeprints.uea.ac.uk/63950/.

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This work proposes a method of model-based speech enhancement that uses a network of HMMs to first decode noisy speech and to then synthesise a set of features that enables a speech production model to reconstruct clean speech. The motivation is to remove the distortion and residual and musical noises that are associated with conventional filteringbased methods of speech enhancement. STRAIGHT forms the speech production model for speech reconstruction and requires a time-frequency spectral surface, aperiodicity and a fundamental frequency contour. The technique of HMM-based synthesis is used t

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12

Van, Gael Jurgen. "Bayesian nonparametric hidden Markov models." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610196.

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13

Lystig, Theodore C. "Evaluation of hidden Markov models /." Thesis, Connect to this title online; UW restricted, 2001. http://hdl.handle.net/1773/9597.

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14

Stanke, Mario. "Gene prediction with a Hidden Markov model." Doctoral thesis, [S.l.] : [s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=970841310.

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15

Lott, Paul Christian. "StochHMM| A Flexible Hidden Markov Model Framework." Thesis, University of California, Davis, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3602142.

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<p>In the era of genomics, data analysis models and algorithms that provide the means to reduce large complex sets into meaningful information are integral to further our understanding of complex biological systems. Hidden Markov models comprise one such data analysis technique that has become the basis of many bioinformatics tools. Its relative success is primarily due to its conceptually simplicity and robust statistical foundation. Despite being one of the most popular data analysis modeling techniques for classification of linear sequences of data, researchers have few available software o

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16

Yi, Kwan 1963. "Text classification using a hidden Markov model." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=85214.

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Text categorization (TC) is the task of automatically categorizing textual digital documents into pre-set categories by analyzing their contents. The purpose of this study is to develop an effective TC model to resolve the difficulty of automatic classification. In this study, two primary goals are intended. First, a Hidden Markov Model (HAM is proposed as a relatively new method for text categorization. HMM has been applied to a wide range of applications in text processing such as text segmentation and event tracking, information retrieval, and information extraction. Few, however, ha

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17

Beattie, Valerie L. "Hidden Markov Model state-based noise compensation." Thesis, University of Cambridge, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.259519.

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18

Seward, D. C. (DeWitt Clinton). "Graphical analysis of hidden Markov model experiments." Thesis, Massachusetts Institute of Technology, 1994. http://hdl.handle.net/1721.1/36469.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.<br>Includes bibliographical references (leaves 60-61).<br>by DeWitt C. Seward IV.<br>Ph.D.

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19

Schwardt, Ludwig. "Efficient Mixed-Order Hidden Markov Model Inference." Thesis, Link to the online version, 2007. http://hdl.handle.net/10019/709.

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20

Ford, Jason. "Adaptive hidden Markov model estimation and applications." Phd thesis, Australian National University, 1998. http://hdl.handle.net/1885/145631.

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Initially introduced in the late 1960's and early 1970's, hidden Markov models (HMMs) have become increasingly popular in the last decade. The major reason for the increasing popularity of HMMs has been the richness of the model class and the power of the signal processing tools. In this thesis we propose several algorithms for estimation of HMM parameters. Initially, we propose recursive prediction error algorithms for separately estimating the state values and the state transition probability matrix. Local convergence results and corresponding convergence rates are obtained via an ordina

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21

Ford, Jason. "Adaptive hidden Markov model estimation and applications." Thesis, Australian National University, 1998. https://eprints.qut.edu.au/108491/1/jasonford.pdf.

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Abstract (sommario):

Initially introduced in the late 1960's and early 1970's, hidden Markov models (HMMs) have become increasingly popular in the last decade. The major reason for the increasing popularity of HMMs has been the richness of the model class and the power of the signal processing tools. In this thesis we propose several algorithms for estimation of HMM parameters. Initially, we propose recursive prediction error algorithms for separately estimating the state values and the state transition probability matrix. Local convergence results and corresponding convergence rates are obtained via an ordina

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22

Ali, Asif. "Voice query-by-example for resource-limited languages using an ergodic hidden Markov model of speech." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50363.

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An ergodic hidden Markov model (EHMM) can be useful in extracting underlying structure embedded in connected speech without the need for a time-aligned transcribed corpus. In this research, we present a query-by-example (QbE) spoken term detection system based on an ergodic hidden Markov model of speech. An EHMM-based representation of speech is not invariant to speaker-dependent variations due to the unsupervised nature of the training. Consequently, a single phoneme may be mapped to a number of EHMM states. The effects of speaker-dependent and context-induced variation in speech on its EHM

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23

Samaria, Ferdinando Silvestro. "Face recognition using Hidden Markov Models." Thesis, University of Cambridge, 1995. https://www.repository.cam.ac.uk/handle/1810/244871.

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This dissertation introduces work on face recognition using a novel technique based on Hidden Markov Models (HMMs). Through the integration of a priori structural knowledge with statistical information, HMMs can be used successfully to encode face features. The results reported are obtained using a database of images of 40 subjects, with 5 training images and 5 test images for each. It is shown how standard one-dimensional HMMs in the shape of top-bottom models can be parameterised, yielding successful recognition rates of up to around 85%. The insights gained from top-bottom models are extend

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24

Foreman, Lindsay Anne. "Bayesian computation for hidden Markov models." Thesis, Imperial College London, 1994. http://hdl.handle.net/10044/1/11490.

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25

Staples, Jonathan Peter. "Hidden Markov models for credit risk." Thesis, Imperial College London, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440498.

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26

Webb, Alexandra. "Detecting recombination using hidden markov models." Thesis, University of Oxford, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.510259.

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27

Tanguay, Donald O. (Donald Ovila). "Hidden Markov models for gesture recognition." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/37796.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.<br>Includes bibliographical references (p. 41-42).<br>by Donald O. Tanguay, Jr.<br>M.Eng.

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28

Kapadia, Sadik. "Discriminative training of hidden Markov models." Thesis, University of Cambridge, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.624997.

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29

Ballot, Johan Stephen Simeon. "Face recognition using Hidden Markov Models." Thesis, Stellenbosch : University of Stellenbosch, 2005. http://hdl.handle.net/10019.1/2577.

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This thesis relates to the design, implementation and evaluation of statistical face recognition techniques. In particular, the use of Hidden Markov Models in various forms is investigated as a recognition tool and critically evaluated. Current face recognition techniques are very dependent on issues like background noise, lighting and position of key features (ie. the eyes, lips etc.). Using an approach which specifically uses an embedded Hidden Markov Model along with spectral domain feature extraction techniques, shows that these dependencies may be lessened while high recognition ra

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30

Santos, Leonor Marques Pompeu dos. "Hidden Markov models for credit risk." Master's thesis, Instituto Superior de Economia e Gestão, 2015. http://hdl.handle.net/10400.5/11061.

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Mestrado em Matemática Financeira<br>A análise do Risco de Crédito, a avaliação do risco de defafult ou de redução do valor de mercado causado por alterações na qualidade de crédito, tem sido um tema vastamente estudado ao longo dos últimos trinta anos e é hoje mais relevante que nunca, com o mundo ainda a recuperar das consequências de uma crise financeira, na sua génese induzida por uma observação imperfeita deste tipo de risco. Tal como alguns dos modelos apresentados anteriormente, o modelo apresentado nesta dissertação assume que os eventos de default estão directamente ligados a uma var

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31

Anderson, Michael. "Option pricing using hidden Markov models." Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/10045.

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Includes bibliographical references (leaves 144-149).<br>This work will present an option pricing model that accommodates parameters that vary over time, whilst still retaining a closed-form expression for option prices: the Hidden Markov Option Pricing Model. This is possible due to the macro-structure of this model and provides the added advantage of ensuring efficient computation of option prices. This model turns out to be a very natural extension to the Black-Scholes model, allowing for time-varying input parameters.

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32

DESAI, PRANAY A. "SEQUENCE CLASSIFICATION USING HIDDEN MARKOV MODELS." University of Cincinnati / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1116250500.

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33

Durey, Adriane Swalm. "Melody spotting using hidden Markov models." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04082004-180126/unrestricted/durey%5Fadriane%5Fs%5F200312%5Fphd.pdf.

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34

Zhang, Chun. "Hidden Markov models for admixture mapping /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2004. http://uclibs.org/PID/11984.

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35

Maruotti, Antonello. "Hidden Markov Models for longitudinal data." Doctoral thesis, La Sapienza, 2008. http://hdl.handle.net/11573/917431.

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36

Wang, Yijie Dylan. "Hidden Markov model with application in cell adhesion experiment and Bayesian cubic splines in computer experiments." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/49061.

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Estimation of the number of hidden states is challenging in hidden Markov models. Motivated by the analysis of a specific type of cell adhesion experiments, a new frame-work based on hidden Markov model and double penalized order selection is proposed. The order selection procedure is shown to be consistent in estimating the number of states. A modified Expectation-Maximization algorithm is introduced to efficiently estimate parameters in the model. Simulations show that the proposed framework outperforms existing methods. Applications of the proposed methodology to real data demonstrate the

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37

Dannemann, Jörn. "Inference for hidden Markov models and related models." Göttingen Cuvillier, 2009. http://d-nb.info/1000750442/04.

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38

Marklund, Emil. "Bayesian inference in aggregated hidden Markov models." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-243090.

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Single molecule experiments study the kinetics of molecular biological systems. Many such studies generate data that can be described by aggregated hidden Markov models, whereby there is a need of doing inference on such data and models. In this study, model selection in aggregated Hidden Markov models was performed with a criterion of maximum Bayesian evidence. Variational Bayes inference was seen to underestimate the evidence for aggregated model fits. Estimation of the evidence integral by brute force Monte Carlo integration theoretically always converges to the correct value, but it conver

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39

The, Yu-Kai. "Analysis of ion channels with hidden Markov models." [S.l.] : [s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=976048744.

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40

Chou, Lin-Yi. "Improving the performance of Hierarchical Hidden Markov Models on Information Extraction tasks." The University of Waikato, 2006. http://adt.waikato.ac.nz/public/adt-uow20070212.152608/index.html.

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41

Farges, Eric P. "An analysis-synthesis hidden Markov model of speech." Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/14775.

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42

Dey, Arkajit. "Hidden Markov model analysis of subcellular particle trajectories." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66307.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student submitted PDF version of thesis.<br>Includes bibliographical references (p. 71-73).<br>How do proteins, vesicles, or other particles within a cell move? Do they diffuse randomly or ow in a particular direction? Understanding how subcellular particles move in a cell will reveal fundamental principles of cel

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43

Le, Riche Pierre (Pierre Jacques). "Handwritten signature verification : a hidden Markov model approach." Thesis, Stellenbosch : Stellenbosch University, 2000. http://hdl.handle.net/10019.1/51784.

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Thesis (MEng)--University of Stellenbosch, 2000.<br>ENGLISH ABSTRACT: Handwritten signature verification (HSV) is the process through which handwritten signatures are analysed in an attempt to determine whether the person who made the signature is who he claims to be. Banks and other financial institutions lose billions of rands annually to cheque fraud and other crimes that are preventable with the aid of good signature verification techniques. Unfortunately, the volume of cheques that are processed precludes a thorough HSV process done in the traditional manner by human operators. It

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44

Huda, Shamsul. "Hybrid training approaches to Hidden Markov Model-based acoustic models for automatic speech recognition." Thesis, University of Ballarat, 2008. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/39435.

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45

Liu, Nianjun. "Hand gesture recognition by Hidden Markov Models /." [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18158.pdf.

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46

Florez-Larrahondo, German. "Incremental learning of discrete hidden Markov models." Diss., Mississippi State : Mississippi State University, 2005. http://library.msstate.edu/etd/show.asp?etd=etd-05312005-141645.

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47

Lancaster, Joseph Paul Jr. "Toward autism recognition using hidden Markov models." Thesis, Manhattan, Kan. : Kansas State University, 2008. http://hdl.handle.net/2097/777.

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48

Austin, Stephen Christopher. "Hidden Markov models for automatic speech recognition." Thesis, University of Cambridge, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.292913.

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49

Larson, Jessica. "Hidden Markov Models Predict Epigenetic Chromatin Domains." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10105.

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Epigenetics is an important layer of transcriptional control necessary for cell-type specific gene regulation. We developed computational methods to analyze the combinatorial effect and large-scale organizations of genome-wide distributions of epigenetic marks. Throughout this dissertation, we show that regions containing multiple genes with similar epigenetic patterns are found throughout the genome, suggesting the presence of several chromatin domains. In Chapter 1, we develop a hidden Markov model (HMM) for detecting the types and locations of epigenetic domains from multiple histone modi

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50

Kordi, Kamran. "Intelligent character recognition using hidden Markov models." Thesis, Loughborough University, 1990. https://dspace.lboro.ac.uk/2134/13786.

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Recognition of printed and hand printed characters has received much attention over the past decade as the need for automated 'document entry' systems assumes a commanding role in office automation. Although, present Optical Character Recognition(OCR) systems have reached a high degree of sophistication as compared to early systems, the design of a robust system which can separate text from images accurately and cope reliably with noisy input and frequent change of font is a formidable task. In this thesis, a novel method of character recognition based on Hidden Markov Modelling (HMM) is initi

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