Ansätze zur lokalen Bayes’schen Fusion von Informationsbeiträgen heterogener Quellen
Abstract
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.
Keywords
Informationsfusion; heterogene Informationsquellen; Bayes’sche Theorie; Prinzip der Maximalen Entropie; Unsicherheit; information fusion; heterogeneous information sources; Bayesian theory; Maximum Entropy principle; uncertainty; thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientistsISBN
9783731510628Publisher
KIT Scientific PublishingPublisher website
http://www.ksp.kit.edu/Publication date and place
Karlsruhe, 2021Series
Karlsruher Schriften zur Anthropomatik,Classification
Maths for computer scientists
