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pro vyhledávání: '"Godsill, Simon J."'
We consider the smoothing problem for a class of conditionally linear Gaussian state-space (CLGSS) models, referred to as mixed linear/nonlinear models. In contrast to the better studied hierarchical CLGSS models, these allow for an intricate cross d
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93460
This paper proposes a probabilistic framework for the sequential estimation of the likelihood of a driver or passenger(s) returning to the vehicle and time of arrival, from the available partial track of the user location. The latter can be provided
Externí odkaz:
http://arxiv.org/abs/1709.07381
Publikováno v:
IEEE Transactions on Aerospace and Electronic Systems; August 2024, Vol. 60 Issue: 4 p5286-5311, 26p
In several application areas, such as human computer interaction, surveillance and defence, determining the intent of a tracked object enables systems to aid the user/operator and facilitate effective, possibly automated, decision making. In this pap
Externí odkaz:
http://arxiv.org/abs/1508.06115
Sequential Monte Carlo (SMC) methods, such as the particle filter, are by now one of the standard computational techniques for addressing the filtering problem in general state-space models. However, many applications require post-processing of data
Externí odkaz:
http://arxiv.org/abs/1505.06357
Akademický článek
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Publikováno v:
Journal of the Royal Statistical Society. Series B (Statistical Methodology), 2004 Jan 01. 66(3), 575-589.
Externí odkaz:
https://www.jstor.org/stable/3647496
Autor:
Godsill, Simon J.
Publikováno v:
Journal of Computational and Graphical Statistics, 2001 Jun 01. 10(2), 230-248.
Externí odkaz:
https://www.jstor.org/stable/1391010
Autor:
Godsill, Simon J.
Publikováno v:
International Statistical Review / Revue Internationale de Statistique, 1997 Apr 01. 65(1), 1-21.
Externí odkaz:
https://www.jstor.org/stable/1403430