Exact Approximation of Rao-Blackwellised Particle Filters*
نویسندگان
چکیده
منابع مشابه
Exact Approximation of Rao - Blackwellised Particle Filters ?
Particle methods are a category of Monte Carlo algorithms that have become popular for performing inference in non-linear non-Gaussian state-space models. The class of “RaoBlackwellised” particle filters exploits the analytic marginalisation that is possible for some statespace models to reduce the variance of the Monte Carlo estimates. Despite being applicable to only a restricted class of sta...
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We tackle the fault diagnosis problem using conditionally Gaussian state space models and an efficient Monte Carlo method known as Rao-Blackwellised particle filtering. In this setting, there is one different linearGaussian state space model for each possible discrete state of operation. The task of diagnosis is to identify the discrete state of operation using the continuous measurements corru...
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Arnaud Doucet EE Engineering University of Melbourne Parkville, Victoria 3052 Australia [email protected] In this paper, we extend the Rao-Blackwellised particle filtering method to more complex hybrid models consisting of Gaussian latent variables and discrete observations. This is accomplished by augmenting the models with artificial variables that enable us to apply Rao-Blackwellisation. Ot...
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Estimating the location of people using a network of sensors placed throughout an environment is a fundamental challenge in smart environments and ubiquitous computing. Id-sensors such as infrared badges provide explicit object identity information but coarse location information while anonymous sensors such as laser range-finders provide accurate location information only. Tracking using both ...
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ژورنال
عنوان ژورنال: IFAC Proceedings Volumes
سال: 2012
ISSN: 1474-6670
DOI: 10.3182/20120711-3-be-2027.00183