Linear Fusion of Estimators with Gaussian Mixture Errors under Unknown Dependences

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F14%3A43922866" target="_blank" >RIV/49777513:23520/14:43922866 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6916140" target="_blank" >http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6916140</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Linear Fusion of Estimators with Gaussian Mixture Errors under Unknown Dependences

Popis výsledku v původním jazyce

In decentralised state estimation, there are two key problems. The first one is how to fuse estimators that are given by the local processing of locally obtained data. The second one is to compute the description of the fused estimator error supposing the fusion rule is specified. Alternatively, if the global knowledge of the decentralised problem is not available, the second problem may be to provide such a description that does not overvalue the quality of the fused estimator. The last problem is followed in this paper. For local estimator errors with Gaussian mixture densities, an underlying joint Gaussian mixture is supposed. The component indices of the joint Gaussian mixture are supposed to be hidden discrete random variables with unknown probability function. The estimator fusion is considered to be linear with fixed weights. An upper bound of the mean square error matrix of the fused estimator is designed. In a case study, the newly designed upper bound is compared with a curre

Název v anglickém jazyce

Linear Fusion of Estimators with Gaussian Mixture Errors under Unknown Dependences

Popis výsledku anglicky

In decentralised state estimation, there are two key problems. The first one is how to fuse estimators that are given by the local processing of locally obtained data. The second one is to compute the description of the fused estimator error supposing the fusion rule is specified. Alternatively, if the global knowledge of the decentralised problem is not available, the second problem may be to provide such a description that does not overvalue the quality of the fused estimator. The last problem is followed in this paper. For local estimator errors with Gaussian mixture densities, an underlying joint Gaussian mixture is supposed. The component indices of the joint Gaussian mixture are supposed to be hidden discrete random variables with unknown probability function. The estimator fusion is considered to be linear with fixed weights. An upper bound of the mean square error matrix of the fused estimator is designed. In a case study, the newly designed upper bound is compared with a curre

Druh

D - Stať ve sborníku

CEP obor

BC - Teorie a systémy řízení

OECD FORD obor

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Projekt

<a href="/cs/project/GC13-07058J" target="_blank" >GC13-07058J: Konzervativní fúze v systémech odhadu propojených v síti</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 17th International Conference on Information Fusion

ISBN

978-84-9012-355-3

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

1-8

Název nakladatele

IEEE

Místo vydání

Salamanca

Místo konání akce

Salamanca, Spain

Datum konání akce

7. 7. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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