On Convergence of Kernel Density Estimates in Particle Filtering

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F16%3A00469752" target="_blank" >RIV/67985807:_____/16:00469752 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.14736/kyb-2016-5-0735" target="_blank" >http://dx.doi.org/10.14736/kyb-2016-5-0735</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.14736/kyb-2016-5-0735" target="_blank" >10.14736/kyb-2016-5-0735</a>

Result language
angličtina
Original language name
On Convergence of Kernel Density Estimates in Particle Filtering
Original language description
The paper deals with kernel density estimates of filtering densities in the particle filter. The convergence of the estimates is investigated by means of Fourier analysis. It is shown that the estimates converge to the theoretical filtering densities in the mean integrated squared error. An upper bound on the convergence rate is given. The result is provided under a certain assumption on the Sobolev character of the filtering densities. A sufficient condition is presented for the persistence of this Sobolev character over time.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BB - Applied statistics, operational research
OECD FORD branch
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Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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