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Communication Dans Un Congrès Année : 2014

Underdetermined Magnetostatic Inverse Problem : Bayes Theorem application

Résumé

This paper deals with the use of the Bayesian approach to inverse an underdetermined problem. The modeled a priori information is statistically studied using either Unscented Transform (UT) method or Monte Carlo (MC) method to estimate the mean value and standard deviation. The whole approach is applied to an experimental setup illustrating an electric vehicle power circuitry. This demonstrates the strength of coupling modeling and measurements for complex systems identification. Keywords: Bayes theorem, Inverse problem, Magnetostatic, Monte Carlo, Unscented Transform
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Dates et versions

hal-01064541 , version 1 (16-09-2014)

Identifiants

  • HAL Id : hal-01064541 , version 1

Citer

Olivier Pinaud, Olivier Chadebec, Laure-Line Rouve, Jean-Louis Coulomb, Jean-Michel Guichon. Underdetermined Magnetostatic Inverse Problem : Bayes Theorem application. OIPE 2014 (Optimisation and Inverse Problem in Electromagnetism), Sep 2014, Delft, Netherlands. ⟨hal-01064541⟩
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