Search for dissertations about: "Sequential Monte Carlo method"

Showing result 1 - 5 of 19 swedish dissertations containing the words Sequential Monte Carlo method.

  1. 1. Sequential Monte Carlo for inference in nonlinear state space models

    University dissertation from Linköping : Linköping University Electronic Press

    Author : Johan Dahlin; Thomas Schön; Fredrik Lindsten; Adam M. Johansen; [2014]

    Abstract : Nonlinear state space models (SSMs) are a useful class of models to describe many different kinds of systems. Some examples of its applications are to model; the volatility in financial markets, the number of infected persons during an influenza epidemic and the annual number of major earthquakes around the world. READ MORE

  2. 2. On inference in partially observed Markov models using sequential Monte Carlo methods

    University dissertation from Linköping : Linköping University Electronic Press

    Author : Jonas Ströjby; [2010]

    Abstract : This thesis concerns estimation in partially observed continuous and discrete time Markov models and focus on both inference about the conditional distribution of the unobserved process as well as parameter inference for the dynamics of the unobserved process. Paper A concerns calibration of advanced stock price models, in particular the Bates and NIG-CIR models, using options data observed through bid-ask spreads. READ MORE

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

    University dissertation from Department of Mathematical Statistics, Lund University

    Author : Svetlana Bizjajeva; [2008]
    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

  4. 4. Acoustic Sound Source Localisation and Tracking in Indoor Environments

    University dissertation from Karlskrona : Blekinge Institute of Technology

    Author : Anders Johansson; [2008]
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Room acoustics; Speaker localisation; Tracking; State-space filter; Sequential Monte Carlo method; Particle filter;

    Abstract : With advances in micro-electronic complexity and fabrication, sophisticated algorithms for source localisation and tracking can now be deployed in cost sensitive appliances for both consumer and commercial markets. As a result, such algorithms are becoming ubiquitous elements of contemporary communication, robotics and surveillance systems. READ MORE

  5. 5. Machine learning with state-space models, Gaussian processes and Monte Carlo methods

    University dissertation from Uppsala : Acta Universitatis Upsaliensis

    Author : Andreas Svensson; Thomas B. Schön; Fredrik Lindsten; Carl Edward Rasmussen; [2018]
    Keywords : TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; NATURVETENSKAP; NATURAL SCIENCES; Machine learning; State-space models; Gaussian processes; Elektroteknik med inriktning mot reglerteknik; Electrical Engineering with specialization in Automatic Control;

    Abstract : Numbers are present everywhere, and when they are collected and recorded we refer to them as data. Machine learning is the science of learning mathematical models from data. Such models, once learned from data, can be used to draw conclusions, understand behavior, predict future evolution, and make decisions. READ MORE