Number of the records: 1
Point-mass filter with functional decomposition of transient density and two-level convolution
- 1.
SYSNO ASEP 0574015 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Point-mass filter with functional decomposition of transient density and two-level convolution Author(s) Straka, O. (CZ)
Duník, J. (CZ)
Tichavský, Petr (UTIA-B) RID, ORCIDNumber of authors 3 Source Title IFAC-PapersOnLine. Volume 56, Issue 2 - 22nd IFAC World Congress. - Amsterdam : Elsevier, 2023 - ISSN 2405-8963 Pages s. 7516-7520 Number of pages 6 s. Publication form Print - P Action 22nd IFAC World Congress Event date 09.07.2023 - 14.07.2023 VEvent location Yokohama Country JP - Japan Event type WRD Language eng - English Country AT - Austria Keywords bayesian methods ; state estimation ; transient density Subject RIV BB - Applied Statistics, Operational Research OECD category Automation and control systems R&D Projects GA22-11101S GA ČR - Czech Science Foundation (CSF) Institutional support UTIA-B - RVO:67985556 EID SCOPUS 85184959563 DOI https://doi.org/10.1016/j.ifacol.2023.10.509 Annotation The paper deals with Bayesian state estimation using the point-mass filter with a particular focus on the prediction step involving the convolution of two grids of points. To reduce the computational costs of the step, a functional decomposition-based convolution was proposed by Tichavský et al. (2022), which approximates the transient probability density function (PDF) over an approximation region. This paper addresses the problem of having spacious grids of points due to state uncertainty while the approximation region is kept small to preserve low computational complexity. A two-level convolution is proposed based on splitting the grids into sub-grids and processing the convolution in the upper level for the sub-grids and in the lower level for their points. A numerical example demonstrates the efficiency of the proposed technique. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2024
Number of the records: 1