Sökning: "Covariance fitting"
Visar resultat 6 - 10 av 13 avhandlingar innehållade orden Covariance fitting.
6. Identification of viscoelastic materials and continuous-time stochastic systems
Sammanfattning : Two system identification problems, identification of viscoelastic material properties and identification of continuous-time stochastic systems, are considered in the thesis. The viscoelastic material properties are characterised by the frequency-dependent complex modulus. LÄS MER
7. Estimation Using Low Rank Signal Models
Sammanfattning : Designing estimators based on low rank signal models is a common practice in signal processing. Some of these estimators are designed to use a single low rank snapshot vector, while others employ multiple snapshots. This dissertation deals with both these cases in different contexts. LÄS MER
8. Noise Convolution Models: Fluids in Stochastic Motion, Non-Gaussian Tempo-Spatial Fields, and a Notion of Tilting
Sammanfattning : The primary topic of this thesis is a class of tempo-spatial models which are rather flexible in a distributional sense. They prove quite successful in modeling (temporal) dependence structures and go beyond the limitation of Gaussian models, thus allowing for heavy tails and skewness. LÄS MER
9. Group-Sparse Regression : With Applications in Spectral Analysis and Audio Signal Processing
Sammanfattning : 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. LÄS MER
10. On performance analysis of subspace methods in system identification and sensor array processing
Sammanfattning : This thesis addresses the issue of performance analysis of subspace-based parameter estimation methods in two different applications, namely system identification and sensor array processing. The objective is to study the quality of the estimated models as the amount of data increases, and to suggest improvements and give user guidelines. LÄS MER