Neural Augmented Adaptive Grid Design for Point-Mass Filter
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F25%3A43976520" target="_blank" >RIV/49777513:23520/25:43976520 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ICCC65605.2025.11022956" target="_blank" >https://doi.org/10.1109/ICCC65605.2025.11022956</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICCC65605.2025.11022956" target="_blank" >10.1109/ICCC65605.2025.11022956</a>
Alternative languages
Result language
angličtina
Original language name
Neural Augmented Adaptive Grid Design for Point-Mass Filter
Original language description
This paper deals with the state estimation of nonlinear systems described by dynamic stochastic state-space models using a point-mass filter (PMF). The PMF is based on the approximation of the conditional probability density function by a piece-wise constant probability density, called the point-mass density (PMD), where the probability is evaluated at N grid points. The number of grid points significantly affects both the performance and computational complexity of the PMF. However, N is typically regarded as a user-defined parameter. The aim of this paper is to augment the PMF with a neural network (NN). This NN selects the smallest N that leads to the required estimation accuracy thus ensuring the minimal computational complexity.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/GC25-16919J" target="_blank" >GC25-16919J: Advanced State Estimation for High Dimensional Multitarget Tracking</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2025 26th International Carpathian Control Conference (ICCC)
ISBN
979-8-3315-0127-3
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
1-6
Publisher name
IEEE
Place of publication
Starý Smokovec
Event location
Starý Smokovec, Slovensko
Event date
May 19, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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