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%2F67985807%3A_____%2F20%3A00505260" target="_blank" >RIV/67985807:_____/20:00505260 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-030-18058-4_27" target="_blank" >http://dx.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

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

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

978-3-030-18057-7

ISSN

2194-5357

e-ISSN

—

Number of pages

8

Pages from-to

339-346

Publisher name

Springer

Place of publication

Cham

Event location

Cracow

Event date

Jul 2, 2018

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000493382100027