Sökning: "Particle Smoother"

Visar resultat 1 - 5 av 16 avhandlingar innehållade orden Particle Smoother.

1. 1. Particle filters and Markov chains for learning of dynamical systems

   Författare :Fredrik Lindsten; Thomas B. Schön; Lennart Ljung; Fredrik Gustafsson; Arnaud Doucet; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Bayesian learning; System identification; Sequential Monte Carlo; Markov chain Monte Carlo; Particle MCMC; Particle filters; Particle smoothers;

   Sammanfattning : 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. LÄS MER

3. 2. Particle Coating in a Wurster Type Bed

   Författare :Stina Karlsson; Chalmers tekniska högskola; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Drying; Particle; Tracking technique; Spouted bed; Fluidisation; Multiphase flow; CFD; Trajectory; Coating; Wurster;

   Sammanfattning : 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. LÄS MER

4. 3. Bayesian Inference for Nonlinear Dynamical Systems : Applications and Software Implementation

   Författare :Jerker Nordh; Institutionen för reglerteknik; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Indoor Navigation; pyParticleEst; Software Implementation; Simultaneous Localization and Mapping; Parameter Estimation; System Identification; Sequential Importance Sampling; Particle Filter; Bayesian Inference; Markov Chain Monte Carlo; Particle Smoother;

   Sammanfattning : 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. LÄS MER

5. 4. Laser-Driven Particle Acceleration - Improving Performance Through Smart Target Design

   Författare :Matthias Burza; Atomfysik; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; wakefield; ultra-relativistic; ultra-intense; TNSA; Terawatt; sheath; proton; polarimetry; plasma mirror; plasma; Petawatt; particle; oscillation; Normarski; micromachining; LWFA; laser; interferometry; electron; contrast; acceleration; bubble; Fysicumarkivet A:2012:Burza;

   Sammanfattning : 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. LÄS MER

7. 5. Estimation of Nonlinear Dynamic Systems : Theory and Applications

   Författare :Thomas B. Schön; Fredrik Gustafsson; Simon Godsill; Linköpings universitet; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Nonlinear estimation; system identification; Kalman filter; particle filter; marginalized particle filter; expectation maximization; automotive applications; Automatic control; Reglerteknik;

   Sammanfattning : 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. LÄS MER