Skip to Main content Skip to Navigation
Preprints, Working Papers, ...

Fast state estimation in nonlinear parametric time dependent systems using Tensor Train

Damiano Lombardi 1
1 COMMEDIA - COmputational Mathematics for bio-MEDIcal Applications
Inria de Paris, LJLL (UMR_7598) - Laboratoire Jacques-Louis Lions
Abstract : In the present work we propose a reduced-order method to solve the state estimation problem when nonlinear parametric time-dependent systems are at hand. The method is based on the approximation of the set of system solutions by means of a Tensor Train format. The particular structure of Tensor Train makes it possible to set up both a variational and a sequential method. Several numerical experiments are proposed to assess the behaviour of the method.
Document type :
Preprints, Working Papers, ...
Complete list of metadata

https://hal.inria.fr/hal-03375811
Contributor : Damiano Lombardi Connect in order to contact the contributor
Submitted on : Wednesday, October 13, 2021 - 9:47:58 AM
Last modification on : Saturday, December 4, 2021 - 4:08:17 AM

File

art_TTStateEst.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03375811, version 1

Citation

Damiano Lombardi. Fast state estimation in nonlinear parametric time dependent systems using Tensor Train. 2021. ⟨hal-03375811⟩

Share

Metrics

Record views

72

Files downloads

60