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On Visualisation of Linear Estimation and Fusion: From Equations to Ellipses

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43969665" target="_blank" >RIV/49777513:23520/23:43969665 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1109/SDF-MFI59545.2023.10361360" target="_blank" >https://doi.org/10.1109/SDF-MFI59545.2023.10361360</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/SDF-MFI59545.2023.10361360" target="_blank" >10.1109/SDF-MFI59545.2023.10361360</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On Visualisation of Linear Estimation and Fusion: From Equations to Ellipses

  • Original language description

    Visualisation of mathematical objects often leads to faster and easier comprehension of theories. On the other hand, deriving conclusions exclusively from a graphical interpretation can be misleading. A typical case in estimation is an ellipse, which corresponds to contour lines of a bivariate Gaussian density. This paper combines insights from various areas. Algebraic relations are presented first, geometric objects are shown subsequently. Constructions of ellipses by determining radii and positions of tangent lines are discussed. The stress is laid on exposition of linear estimation with a focus on methodology of fusion of estimates, especially in the case when cross-correlations of estimation errors are not fully known. The exposition also covers multidimensional variables, where the ellipses become ellipsoids.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the 2023 IEEE Symposium Sensor Data Fusion and International Conference on Multisensor Fusion and Integration (SDF-MFI)

  • ISBN

    979-8-3503-8258-7

  • ISSN

  • e-ISSN

    2767-9357

  • Number of pages

    6

  • Pages from-to

  • Publisher name

    IEEE

  • Place of publication

    Bonn, Německo

  • Event location

    Bonn, Německo

  • Event date

    Nov 27, 2023

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article