Sökning: "Numerical regularization"
Visar resultat 11 - 15 av 51 avhandlingar innehållade orden Numerical regularization.
11. Utilizing Problem Structure in Optimization of Radiation Therapy
Sammanfattning : In this thesis, optimization approaches for intensity-modulated radiation therapy are developed and evaluated with focus on numerical efficiency and treatment delivery aspects. The first two papers deal with strategies for solving fluence map optimization problems efficiently while avoiding solutions with jagged fluence profiles. LÄS MER
12. Modelling of Delamination Growth in Composite Structures
Sammanfattning : Delaminations constitute an important damage and failure mode in polymeric composite laminates. In order to explicitly incorporate and model the delamination progression within a finite element analysis, the meso-modelling concept is applied in the present work. The laminate is thereby represented by separate layers connected with interfaces. LÄS MER
13. 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
14. High-order finite element methods for incompressible variable density flow
Sammanfattning : The simulation of fluid flow is a challenging and important problem in science and engineering. This thesis primarily focuses on developing finite element methods for simulating subsonic two-phase flows with varying densities, described by the variable density incompressible Navier-Stokes equations. LÄS MER
15. Sequential Data Learning, Scalable Models and Adversarial Regularization
Sammanfattning : Time Series Prediction (TSP) has been used in mobile network traffic data analysis to produce predictive results for network planning and resource allocation. In the first part of this thesis, we propose a novel method of predicting mobile network traffic using neural networks based on conditional probability modeling between adjacent data windows in the time series sequence. LÄS MER