Hierarchical proportional redistribution for bba approximation

Dezert, J. ; Han, D. ; Liu, Z. ; Tacnet, J.M.

Type de document
Communication scientifique avec actes
Langue
Anglais
Affiliation de l'auteur
ONERA PALAISEAU FRA ; XI'AN JIAOTONG UNIVERSITY CHN ; NORTH WESTERN POLYTECHNICAL UNIVERSITY XI'AN CHN ; IRSTEA GRENOBLE UR ETGR FRA
Année
2012
Résumé / Abstract
Dempster’s rule of combination is commonly used in the field of information fusion when dealing with belief functions. However, it generally requires a high computational cost. To reduce it, a basic belief assignment (bba) approximation is needed. In this paper we present a new bba approximation approach called hierarchical proportional redistribution (HPR) allowing to approximate a bba at any given level of non-specificity. Two examples are given to show how our new HPR works.
Congrès
2nd International Conference on Belief Functions, 09/05/2012 - 11/05/2012, Compiègne, FRA
Document d'origine
Belief Functions: Theory and Applications. Advances in Intelligent and Soft Computing. Denoeux T., Masson MH. (eds)
Editeur
Springer

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