On Persistence of Convergence of Kernel Density Estimates in Particle Filtering

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10454992" target="_blank" >RIV/00216208:11320/20:10454992 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-18058-4_27" target="_blank" >https://doi.org/10.1007/978-3-030-18058-4_27</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-18058-4_27" target="_blank" >10.1007/978-3-030-18058-4_27</a>

Result language
angličtina
Original language name
On Persistence of Convergence of Kernel Density Estimates in Particle Filtering
Original language description
A sufficient condition is provided for keeping the character of the filtering density in the filtering task. This is done for the Sobolev class of filtering densities. As a consequence, estimating the filtering density in particle filtering persists its convergence at any time of filtering. Specifying the condition complements previous results on using the kernel density estimates in particle filtering.
Czech name
—
Czech description
—

Project
<a href="/en/project/EF16_013%2F0001787" target="_blank" >EF16_013/0001787: Collaboration on Fermilab experiments</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
INFORMATION TECHNOLOGY, SYSTEMS RESEARCH, AND COMPUTATIONAL PHYSICS
ISBN
978-3-030-18058-4
ISSN
2194-5357
e-ISSN
2194-5365
Number of pages
8
Pages from-to
339-346
Publisher name
SPRINGER INTERNATIONAL PUBLISHING AG
Place of publication
CHAM
Event location
Krakow
Event date
Jul 2, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000493382100027

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