On Fusion of Partial Estimates Under Implicit Partial Knowledge of Correlation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43956249" target="_blank" >RIV/49777513:23520/19:43956249 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9011251" target="_blank" >https://ieeexplore.ieee.org/document/9011251</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
On Fusion of Partial Estimates Under Implicit Partial Knowledge of Correlation
Original language description
Covariance Intersection fusion is bound-optimal under unknown correlations. Partial knowledge can improve the fusion. An implicit constraint on correlation has been introduced in the literature for full-vector estimates. This paper considers fusion of partial estimates. Weak and strong counterparts of the full-vector assumption are proposed. An analysis of admissible ideal fusions reveals that the considered implicit partial knowledge cannot improve the Covariance Intersection fusion of partial estimates. An exception is found for the strong assumption and fusion of one partial and one full-vector estimate. For this case, an improved fusion rule is presented.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
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 2019 22th International Conference on Information Fusion (FUSION)
ISBN
978-0-9964527-8-6
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
1-8
Publisher name
IEEE
Place of publication
Ottawa
Event location
Ottawa, Kanada
Event date
Jul 2, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000567728800094