Search for dissertations about: "non-gaussian state space models"

Showing result 1 - 5 of 8 swedish dissertations containing the words non-gaussian state space models.

  2. 1. Toward Sequential Data Assimilation for NWP Models Using Kalman Filter Tools

    Author : Jelena Bojarova; Rolf Sundberg; Krzysztof Podgorski; Stockholms universitet; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; non-Gaussian state space models; Kalman filtering; ETKF; 3D-Var; data assimilation; NWP; Mathematical statistics; Matematisk statistik; matematisk statistik; Mathematical Statistics;

    Abstract : The aim of the meteorological data assimilation is to provide an initial field for Numerical Weather Prediction (NWP) and to sequentially update the knowledge about it using available observations. Kalman filtering is a robust technique for the sequential estimation of the unobservable model state based on the linear regression concept. READ MORE

  4. 2. Sequential Monte Carlo Methods with Applications to Positioning and Tracking in Wireless Networks

    Author : Svetlana Bizjajeva; Matematisk statistik; []
    Keywords : NATURVETENSKAP; NATURAL SCIENCES; positioning; state-space models; SMCM; particle filtering;

    Abstract : This thesis is based on 5 papers exploring the filtering problem in non-linear non-Gaussian state-space models together with applications of Sequential Monte Carlo (also called particle filtering) methods to the positioning in wireless networks. The aim of the first paper is to study the performance of particle filtering techniques in mobile positioning using signal strength measurements. READ MORE

  5. 3. Credit risk and forward price models

    Author : Raquel M Gaspar; Handelshögskolan i Stockholm; []
    Keywords : SAMHÄLLSVETENSKAP; SOCIAL SCIENCES;

    Abstract : This thesis consists of three distinct parts. Part I introduces the basic concepts and the notion of general quadratic term structures (GQTS) essential in some of the following chapters. Part II focuses on credit risk models and Part III studies forward price term structure models using both the classical and the geometrical approach. READ MORE

  6. 4. Particle filters and Markov chains for learning of dynamical systems

    Author : Fredrik Lindsten; Thomas B. Schön; Lennart Ljung; Fredrik Gustafsson; Arnaud Doucet; Linköpings universitet; []
    Keywords : 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;

    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

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

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

    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