Search for dissertations about: "sparse theory"
Showing result 1 - 5 of 73 swedish dissertations containing the words sparse theory.
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1. Sparse Modeling of Harmonic Signals
Abstract : This thesis considers sparse modeling and estimation of multi-pitch signals, i.e., signals whose frequency content can be described by superpositions of harmonic, or close-to-harmonic, structures, characterized by a set of fundamental frequencies. READ MORE
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2. Sparse Modeling Heuristics for Parameter Estimation - Applications in Statistical Signal Processing
Abstract : This thesis examines sparse statistical modeling on a range of applications in audio modeling, audio localizations, DNA sequencing, and spectroscopy. In the examined cases, the resulting estimation problems are computationally cumbersome, both as one often suffers from a lack of model order knowledge for this form of problems, but also due to the high dimensionality of the parameter spaces, which typically also yield optimization problems with numerous local minima. READ MORE
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3. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing
Abstract : This doctorate thesis focuses on sparse regression, a statistical modeling tool for selecting valuable predictors in underdetermined linear models. By imposing different constraints on the structure of the variable vector in the regression problem, one obtains estimates which have sparse supports, i.e. READ MORE
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4. Sparse Modeling of Grouped Line Spectra
Abstract : This licentiate thesis focuses on clustered parametric models for estimation of line spectra, when the spectral content of a signal source is assumed to exhibit some form of grouping. Different from previous parametric approaches, which generally require explicit knowledge of the model orders, this thesis exploits sparse modeling, where the orders are implicitly chosen. READ MORE
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5. On the Measurement of Model Fit for Sparse Categorical Data
Abstract : This thesis consists of four papers that deal with several aspects of the measurement of model fit for categorical data. In all papers, special attention is paid to situations with sparse data. READ MORE