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Showing 1 to 20 of 314 for “"Markov model"”.
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Hidden Markov model based visual speech recognition
… are presented. Classifiers based on Hidden Markov Model (HMM) are first explored for modeling and identifying the basic visual speech elements. Considering that the temporal features of visual speech elements may be confusable and sensitive to their contexts, three novel training strategies, …
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Face recognition using hidden Markov model supervectors
This project attempts to boost the results of face recognition algorithms already established to perform face recognition by augmenting the architecture and using HMM-based supervector classification. In this thesis, the work of Tang’s 2010 dissertation is used such that the HMM based classifier …
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Graphical analysis of hidden Markov model experiments
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1994.
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Hidden Markov model analysis of subcellular particle trajectories
… the application of several variants of hidden Markov models (HMMs) to analyzing the trajectories of such particles. And we compare the performance of our proposed algorithms with traditional approaches that involve fitting a mean square displacement (MSD) curve calculated from the particle …
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Separation of simultaneous word sequences using Markov model techniques
… simultaneous conversations through the use of Markov Models. Text samples which represent the conversations to be used as training data are described by a grammar based upon word and word-pair occurences within the text. This grammar is then used to establish a Markov Model for the text. These …
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Hidden Markov Model with Binned Duration and Its Application
<p>Hidden Markov models (HMM) have been widely used in various applications such as speech processing and bioinformatics. However, the standard hidden Markov model requires state occupancy durations to be geometrically distributed, which can be inappropriate in some real-world applications where …
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Markov model methods for discrete sequences and soccer analysis
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-20 without embargo terms
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On improving the forecast accuracy of the hidden Markov model
The forecast accuracy of a hidden Markov model (HMM) may be low due first, to the measure of forecast accuracy being ignored in the parameterestimation method and, second, to overfitting caused by the large number of parameters that must be estimated. A general approach to forecasting is described …
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Development of a comparative Markov model for ship overhaul policies
Thesis: Ocean E., Massachusetts Institute of Technology, Department of Ocean Engineering, 1972
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Meta State Generalized Hidden Markov Model for Eukaryotic Gene Structure Identification
Using a generalized-clique hidden Markov model (HMM) as the starting point for a eukaryotic gene finder, the objective here is to strengthen the signal information at the transitions between coding and non-coding (c/nc) regions. This is done by enlarging the primitive hidden states associated with …
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A Markov Model for Admissions of New Students: A Theoretical Study
Made available in DSpace on 2014-12-10T23:08:48Z (GMT). No. of bitstreams: 1 7212391.pdf: 5203089 bytes, checksum: f92c98c9833cd5ba29fc0f9fad504168 (MD5) Previous issue date: 1971
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A multilevel logistic hidden Markov model for learning under cognitive diagnosis
… we propose a multilevel logistic hidden Markov model for learning based on cognitive diagnosis models, where the probability that a learner acquires the target skill depends not only on the general difficulty of the skill and the learner's mastery of other skills in the curriculum, but …
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Hidden Markov Model inference copy number change in array-CGH data
Cancer development and progression typically features genomic instability frequently resulting in genomic changes involving DNA copy number gains or losses. Identifying the genomic location of these regional alterations provides important opportunities for the discovery of potential novel oncogenes …
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The validity of a Markov model of the behaviour of programs
In light of the evidence presented, the modified model has been shown to be valid. However, as with any other validation using test cases, the results cannot be considered a truly formal or general proof of its correctness. However they provide grounds for future work attempting to apply the model, …
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The application of Bayesian adaptive design and Markov model in clinical trials
… and efficacy of the study treatment. Response model and Normal Dynamic Linear Models (NDLMs) are applied in stages 1-4. Conditional probability for each parameter in the model is derived using appropriate prior distributions. Markov Chain Monte Carlo (MCMC) method is used to do the simulation. …
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Application of Hidden Markov Model in Finite Mixture Modeling of High-Dimensional Data
Finite mixture models (FMMs) are widely used in practice and are famous for modeling heterogeneous data in a convenient and effective way. Owing to their flexibility, finitemixtures have since been applied to a wide range of problems in diverse fields, includingimage analysis, medicine, …
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Parameter estimation for a two-state semi-Markov model of a univariate point process.
… interval properties of a two-state semi-Markov model for a univariate point process, an automated technique for the estimation of the parameters in the model was researched and discussed. The power spectral density of intervals was estimated by the periodogram and a Kolmogorov-Smirnov …
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Visualizing speech production with a hidden Markov model tracker to aid speech therapy and communication
… and coherent parts of speech tracked by a hidden Markov model. The goal of these visualizations is to help the user understand speech better by providing a system where users can see the words they speak and experience, develop and practice speech skills using the statistical speech model and …
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