Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Matoušek, Jakub | |
| dc.contributor.author | Brandner, Marek | |
| dc.contributor.author | Duník, Jindřich | |
| dc.date.accessioned | 2023-01-30T11:00:26Z | - |
| dc.date.available | 2023-01-30T11:00:26Z | - |
| dc.date.issued | 2021 | |
| dc.identifier.citation | MATOUŠEK, J. BRANDNER, M. DUNÍK, J. Continuous Nonlinear State Prediction by Finite Volume Method on Logically Rectangular Grids. In Proceedings of the 2021 IEEE 60th IEEE Conference on Decision and Control (CDC). Austin: IEEE, 2021. s. 5890-5895. ISBN: 978-1-66543-659-5 , ISSN: 0743-1546 | cs |
| dc.identifier.isbn | 978-1-66543-659-5 | |
| dc.identifier.issn | 0743-1546 | |
| dc.identifier.uri | 2-s2.0-85126050495 | |
| dc.identifier.uri | http://hdl.handle.net/11025/51149 | |
| dc.format | 6 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | IEEE | |
| dc.relation.ispartofseries | Proceedings of the 2021 IEEE 60th IEEE Conference on Decision and Control (CDC) | en |
| dc.rights | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. | cs |
| dc.rights | © IEEE | en |
| dc.title | Continuous Nonlinear State Prediction by Finite Volume Method on Logically Rectangular Grids | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | ConferenceObject | en |
| dc.rights.access | restrictedAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | This paper deals with the state estimation of the nonlinear stochastic models with continuous dynamics and discrete measurement. Namely, the numerical solution to the Fokker-Planck equation, representing the estimator time update, is explored. Unlike the classical approaches, which use the finite difference method and operate on a standard rectangular grid, this paper utilizes the finite volume method on the logically rectangular grid. In particular, the circular grid is chosen, which better approximates an estimated conditional probability density function support and improves time update accuracy without any impact on its computational complexity. The benefits of the solution are illustrated in a numerical example. | en |
| dc.subject.translated | State estimation | en |
| dc.subject.translated | Bayesian inference | en |
| dc.subject.translated | Nonlinear systems | en |
| dc.identifier.doi | 10.1109/CDC45484.2021.9683293 | |
| dc.type.status | Peer-reviewed | en |
| dc.identifier.document-number | 781990305026 | |
| dc.identifier.obd | 43933466 | |
| dc.project.ID | SGS-2019-020/Rozvoj a využití kybernetických systémů identifikace, diagnostiky a řízení 4 | cs |
| dc.project.ID | EF19_073/0016931/Zvyšování kvality interních grantových schémat na ZČU | cs |
| dc.project.ID | IDEG-IND-2021-002/Numerical Solution to the Fokker-Planck Equation for Navigation System Design | cs |
| Appears in Collections: | Konferenční příspěvky / Conference Papers (KKY) OBD | |
Files in This Item:
| File | Size | Format | |
|---|---|---|---|
| article_CDC2021_MaBrDu.pdf | 1,04 MB | Adobe PDF | View/Open Request a copy |
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