DocumentCode
1167621
Title
Indirect measurement within dynamical context: probabilistic approach to deal with uncertainty
Author
Baili, Hana ; Fleury, Gilles A.
Author_Institution
Dept. of Meas., Ecole Superieure d´´Electr.ite, Gif-sur-Yvette, France
Volume
53
Issue
6
fYear
2004
Firstpage
1449
Lastpage
1454
Abstract
This paper deals with the general question of indirect measurement within dynamical continuous context. The proposed answer is of probabilistic nature in the sense that: the modeling, which is the first element of the answer, consists in transforming the initial model into a stochastic differential equation (SDE) such that, estimating the probability density function (pdf) of its process achieves the measurement, which is indeed the second element of the answer.
Keywords
differential equations; measurement uncertainty; probability; stochastic processes; indirect measurement; knowledge-based model; operational calculus; pdf estimation; probability density function; stochastic differential equations; Calculus; Density measurement; Differential equations; Estimation theory; Integral equations; Performance evaluation; Probability density function; Random variables; Stochastic processes; Time measurement; 65; Indirect measurement; SDEs; estimation; knowledge-based models; operational calculus; pdf; probability density function; stochastic differential equations;
fLanguage
English
Journal_Title
Instrumentation and Measurement, IEEE Transactions on
Publisher
ieee
ISSN
0018-9456
Type
jour
DOI
10.1109/TIM.2004.831138
Filename
1360081
Link To Document