Ansätze zur lokalen Bayes'schen Fusion von Informationsbeiträgen heterogener Quellen

Ansätze zur lokalen Bayes'schen Fusion von Informationsbeiträgen heterogener Quellen

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The solution of various tasks benefits from information fusion or even requires it. The Bayesian fusion methodology is clear, well-founded and fulfills the essential requirements for a meaningful methodology also for fusing the contributions of heterogeneous information sources. In many practically...

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Bibliographic Details
Main Author: Sander, Jennifer (auth)
Format: Electronic Book Chapter
Published: Karlsruhe KIT Scientific Publishing 2021
Series:Karlsruher Schriften zur Anthropomatik
Subjects:
Maths for computer scientists
Informationsfusion
heterogene Informationsquellen
Bayes'sche Theorie
Prinzip der Maximalen Entropie
Unsicherheit
information fusion
heterogeneous information sources
Bayesian theory
Maximum Entropy principle
uncertainty
Online Access:DOAB: download the publication
DOAB: description of the publication
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Summary:The solution of various tasks benefits from information fusion or even requires it. The Bayesian fusion methodology is clear, well-founded and fulfills the essential requirements for a meaningful methodology also for fusing the contributions of heterogeneous information sources. In many practically relevant tasks, Bayesian methods cause high, often unacceptable effort. In the work, novel approaches to cope with Bayesian fusion in such situations are formulated and investigated.
Physical Description:1 electronic resource (342 p.)
ISBN:KSP/1000125447
9783731510628
Access:Open Access

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