Filtering and fixed-point smoothing from an innovation approach in systems with uncertainty.
R. Caballero, A. Hermoso, J. Jiménez, J. Linares (2003)
Extracta Mathematicae
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R. Caballero, A. Hermoso, J. Jiménez, J. Linares (2003)
Extracta Mathematicae
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Chigansky, Pavel, Liptser, Robert (2006)
Electronic Communications in Probability [electronic only]
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Tomasz Rychlik (1995)
Applicationes Mathematicae
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We propose a class of unbiased and strongly consistent nonparametric kernel estimates of a probability density function, based on a random choice of the sample size and the kernel function. The expected sample size can be arbitrarily small and mild conditions on the local behavior of the density function are imposed.
Michael Oberguggenberger, Danijela Rajter-Ćirić (2005)
Publications de l'Institut Mathématique
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Ondřej Straka, Miroslav Šimandl (2011)
Kybernetika
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The paper deals with the particle filter in state estimation of a discrete-time nonlinear non-Gaussian system. The goal of the paper is to design a sample size adaptation technique to guarantee a quality of a filtering estimate produced by the particle filter which is an approximation of the true filtering estimate. The quality is given by a difference between the approximate filtering estimate and the true filtering estimate. The estimate may be a point estimate or a probability density...
Barret, Florent, Bovier, Anton, Méléard, Sylvie (2010)
Electronic Journal of Probability [electronic only]
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Jarnicka, Jolanta (2005)
Zeszyty Naukowe Uniwersytetu Jagiellońskiego. Universitatis Iagellonicae Acta Mathematica
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J, Dinesh Peter., K, Govindan.V., Mathew, Abraham T. (2009)
International Journal of Open Problems in Computer Science and Mathematics. IJOPCM
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Bondarenko, E.M., Topchij, V.A. (2001)
Sibirskij Matematicheskij Zhurnal
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