Search for dissertations about: "Particle filters"
Showing result 1 - 5 of 74 swedish dissertations containing the words Particle filters.
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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 transport in human lung : effects of particle size and shape
Abstract : Recent studies have shown that nanoparticles may be more toxic than larger particles of the same material, but the health risks associated with widespread use largely depend on the extent of exposure. When dealing with potentially toxic particles, precautionary measures have to be taken in order to minimize contact. READ MORE
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3. Stochastic Modeling for Video Object Tracking and Online Learning: manifolds and particle filters
Abstract : Classical visual object tracking techniques provide effective methods when parameters of the underlying process lie in a vector space. However, various parameter spaces commonly occurring in visual tracking violate this assumption. READ MORE
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4. Cavity Field Control for Linear Particle Accelerators
Abstract : High-energy linear particle accelerators enable exploration of the microscopic structure of pharmaceuticals, solar cells, fuel cells, high-temperature superconductors, and the universe itself. These accelerators accelerate charged particles using oscillating magnetic fields that are confined in metal cavities. READ MORE
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5. Accelerating Monte Carlo methods for Bayesian inference in dynamical models
Abstract : Making decisions and predictions from noisy observations are two important and challenging problems in many areas of society. Some examples of applications are recommendation systems for online shopping and streaming services, connecting genes with certain diseases and modelling climate change. READ MORE