Search for dissertations about: "Expectation-Maximization Algorithm"
Showing result 1 - 5 of 43 swedish dissertations containing the words Expectation-Maximization Algorithm.
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1. Towards Asymptotic Vector Quantization
Abstract : We study topics in source coding, and vector quantization (VQ) in particular. We approach VQ from two directions: a theoretical starting point based on high rate quantization theory, and a practical based on a database desription of the signal source. READ MORE
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2. Estimation of Nonlinear Dynamic Systems : Theory and Applications
Abstract : This thesis deals with estimation of states and parameters in nonlinear and non-Gaussian dynamic systems. Sequential Monte Carlo methods are mainly used to this end. These methods rely on models of the underlying system, motivating some developments of the model concept. READ MORE
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3. Probabilistic Models for Species Tree Inference and Orthology Analysis
Abstract : A phylogenetic tree is used to model gene evolution and species evolution using molecular sequence data. For artifactual and biological reasons, a gene tree may differ from a species tree, a phenomenon known as gene tree-species tree incongruence. Assuming the presence of one or more evolutionary events, e.g. READ MORE
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4. Interrogation of Nucleic Acids by Parallel Threading
Abstract : Advancements in the field of biotechnology are expanding the scientific horizon and a promising era is envisioned with personalized medicine for improved health. The amount of genetic data is growing at an ever-escalating pace due to the availability of novel technologies that allow massively parallel sequencing and whole-genome genotyping, that are supported by the advancements in computer science and information technologies. READ MORE
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5. Variational Inference of Dynamic Factor Models
Abstract : When we make difficult and crucial decisions, forecasts are powerful and important tools. For that purpose, statistical models can be our most effective aid. Ideally, these models can incorporate large sets of multifaceted data. READ MORE
