Kalman Filter and Identifiability of the Observation Model
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26210%2F26%3A0200985" target="_blank" >RIV/00216305:26210/26:0200985 - isvavai.cz</a>
Result on the web
<a href="https://www.researchgate.net/profile/Andrej-Srakar/publication/397412266_23rd_European_Young_Statisticians_Meeting_11-15_September_2023_Ljubljana_Slovenia_Proceedings/links/690f2cf1a404d65709a419ee/23rd-European-Young-Statisticians-Meeting-11-15-September-2023-Ljubljana-Slovenia-Proceedings.pdf#page=101" target="_blank" >https://www.researchgate.net/profile/Andrej-Srakar/publication/397412266_23rd_European_Young_Statisticians_Meeting_11-15_September_2023_Ljubljana_Slovenia_Proceedings/links/690f2cf1a404d65709a419ee/23rd-European-Young-Statisticians-Meeting-11-15-September-2023-Ljubljana-Slovenia-Proceedings.pdf#page=101</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Kalman Filter and Identifiability of the Observation Model
Original language description
Kalman filter has become a commonly used approach in many technological applications to filter uncertainty from noisy measurements. In this paper, we describe the Kalman filter as an optimal unbiased estimator of the hidden state in the linear model. Additionally, a discussion of the model estimation is provided. In the end, as an original contribution, a discussion of the observation model is done.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů