Search for dissertations about: "SPECTRAL ESTIMATORS"
Showing result 6 - 10 of 21 swedish dissertations containing the words SPECTRAL ESTIMATORS.
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6. Model-based and matched-filterbank signal analysis
Abstract : The dissertation deals with model-based and matched-filterbank signal analysis. The matched-filterbank (MAFI) spectral estimation approach is introduced, and it is shown that both the amplitude spectrum Capon (ASC) and the amplitude and phase estimation (APES) spectral estimators can be expressed as MAFI spectral estimators. READ MORE
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7. Contributions to Estimation and Testing Block Covariance Structures in Multivariate Normal Models
Abstract : This thesis concerns inference problems in balanced random effects models with a so-called block circular Toeplitz covariance structure. This class of covariance structures describes the dependency of some specific multivariate two-level data when both compound symmetry and circular symmetry appear simultaneously. READ MORE
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8. Estimation for Sensor Fusion and Sparse Signal Processing
Abstract : Progressive developments in computing and sensor technologies during the past decades have enabled the formulation of increasingly advanced problems in statistical inference and signal processing. The thesis is concerned with statistical estimation methods, and is divided into three parts with focus on two different areas: sensor fusion and sparse signal processing. READ MORE
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9. A study of multilevel models with block circular symmetric covariance structures
Abstract : This thesis concerns the study of multilevel models with specific patterned covariance structures and addresses the issues of maximum likelihoodestimation. In particular, circular symmetric hierarchical datastructures are considered. READ MORE
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10. Data driven modeling in the presence of time series structure: : Improved bounds and effective algorithms
Abstract : This thesis consists of five appended papers devoted to modeling tasks where the desired models are learned from data sets with an underlying time series structure. We develop a statistical methodology for providing efficient estimators and analyzing their non-asymptotic behavior. READ MORE