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 :
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