Search for dissertations about: "Particle Smoother"
Showing result 1 - 5 of 16 swedish dissertations containing the words Particle Smoother.
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1. Particle filters and Markov chains for learning of dynamical systems
Abstract : Sequential Monte Carlo (SMC) and Markov chain Monte Carlo (MCMC) methods provide computational tools for systematic inference and learning in complex dynamical systems, such as nonlinear and non-Gaussian state-space models. This thesis builds upon several methodological advances within these classes of Monte Carlo methods. READ MORE
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2. Particle Coating in a Wurster Type Bed
Abstract : The Wurster bed process is frequently used for film coating. In the Wurster bed, particles circulate in the equipment and are sprayed with a liquid which forms a coating when dry. The procedure is repeated until the desired characteristics of the coating layer are obtained. READ MORE
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3. Bayesian Inference for Nonlinear Dynamical Systems : Applications and Software Implementation
Abstract : The topic of this thesis is estimation of nonlinear dynamical systems, focusing on the use of methods such as particle filtering and smoothing. There are three areas of contributions: software implementation, applications of nonlinear estimation and some theoretical extensions to existing algorithms. READ MORE
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4. Laser-Driven Particle Acceleration - Improving Performance Through Smart Target Design
Abstract : Laser-driven particle acceleration makes use of sub-picosecond, pulsed, high-power laser systems, capable of producing intensities ~10^{19} W/cm^2 at the laser focus to form plasmas, and use ultra-relativistic and nonlinear dynamics to produce quasistatic acceleration fields. This allows electrons to be accelerated to ~100 MeV over sub-centimetre distances, while protons may be accelerated to the ~10 MeV regime. READ MORE
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5. 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