 |
Journal articles
Semiparametric estimation of plane similarities: application to fast computation of aeronautic loads
Abstract : In the big data era, it is often needed to resolve the problem of parsimonious data representation. In this paper, the data under study are curves and the sparse representation is based on a semiparametric model. Indeed, we propose an original registration model for noisy curves. The model is built transforming an unknown function by plane similarities. We develop a statistical method that allows to estimate the parameters characterizing the plane similarities. The properties of the statistical procedure are studied. We show the convergence and the asymptotic normality of the estimators. Numerical simulations and a real-life aeronautic example illustrate and demonstrate the strength of our methodology.
Cited literature [28 references]
https://hal.archives-ouvertes.fr/hal-01879135
Contributor : Edouard Fournier <>
Submitted on : Thursday, April 4, 2019 - 2:17:09 PM
Last modification on : Tuesday, October 20, 2020 - 10:32:07 AM
Long-term archiving on: : Friday, July 5, 2019 - 1:53:36 PM
Contributor : Edouard Fournier <>
Submitted on : Thursday, April 4, 2019 - 2:17:09 PM
Last modification on : Tuesday, October 20, 2020 - 10:32:07 AM
Long-term archiving on: : Friday, July 5, 2019 - 1:53:36 PM