• 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