DocumentCode :
3021933
Title :
The principle of possibility maximum specificity as a basis for measurement uncertainty expression
Author :
Mauris, Gilles
Author_Institution :
LISTIC, Univ. de Savoie, Annecy Le Vieux, France
fYear :
2009
fDate :
6-7 July 2009
Firstpage :
5
Lastpage :
9
Abstract :
This paper deals with the foundations of a possibility/fuzzy expression of measurement uncertainty. Indeed the notion of possibility distribution is clearly identified to a family of probability distributions whose coverage intervals are included in the level cuts of the possibility distribution Thus the fuzzy inclusion ordering, dubbed specificity ordering, constitutes the basis of a maximal specificity principle. The latter is sounder than the maximal entropy principle to deal with cases of partial or incomplete information in a measurement context. The two approaches can be compared on some common practical measurement cases thanks to the respective coverage intervals they provide.
Keywords :
maximum entropy methods; measurement uncertainty; statistical distributions; measurement uncertainty expression; possibility maximum specificity; probability distributions; Constraint theory; Entropy; Gaussian distribution; Measurement uncertainty; Possibility theory; Probability density function; Probability distribution; Testing; coverage intervals; maximum entropy principle; maximum specificity principle; measurement uncertainty; possibility theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Methods for Uncertainty Estimation in Measurement, 2009. AMUEM 2009. IEEE International Workshop on
Conference_Location :
Bucharest
Print_ISBN :
978-1-4244-3593-7
Electronic_ISBN :
978-1-4244-3593-7
Type :
conf
DOI :
10.1109/AMUEM.2009.5207599
Filename :
5207599
Link To Document :
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