Diffusion in Lagrangian Grid-based Predictors

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F25%3A43976501" target="_blank" >RIV/49777513:23520/25:43976501 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.23919/FUSION65864.2025.11124123" target="_blank" >https://doi.org/10.23919/FUSION65864.2025.11124123</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.23919/FUSION65864.2025.11124123" target="_blank" >10.23919/FUSION65864.2025.11124123</a>

Result language
angličtina
Original language name
Diffusion in Lagrangian Grid-based Predictors
Original language description
This paper focuses on state prediction for stochastic dynamic models with linear dynamics, emphasizing a recently proposed efficient and robust Lagrangian approach for solving the Chapman-Kolmogorov equation. In contrast to the standard Eulerian perspective, the Lagrangian method separates the solution into two sequential steps: advection and diffusion. Advection is handled by moving a carefully designed grid, while diffusion is addressed using the convolution theorem. This approach significantly reduces computational complexity while preserving the same accuracy. In this paper, we propose formulating diffusion as a continuous-time process, leading to a partial differential equation (PDE). Various methods for solving this PDE are presented and compared within a unified framework, along with evaluations of their properties and example implementations. We demonstrate that the continuous formulation can yield substantial reductions in computational complexity with only marginal loss in accuracy.
Czech name
—
Czech description
—

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)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2025 28th International Conference on Information Fusion (FUSION)
ISBN
978-1-03-705623-9
ISSN
—
e-ISSN
—
Number of pages
8
Pages from-to
1-8
Publisher name
IEEE
Place of publication
Rio de Janiero, Brazílie
Event location
Rio de Janiero, Brazílie
Event date
Jul 7, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—

Similar results(10)