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Journal Articles International Journal for Numerical Methods in Engineering Year : 2022

State estimation in nonlinear parametric time dependent systems using Tensor Train

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.
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Dates and versions

hal-03375811 , version 1 (13-10-2021)
hal-03375811 , version 2 (29-06-2022)
hal-03375811 , version 3 (12-07-2022)

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Cite

Damiano Lombardi. State estimation in nonlinear parametric time dependent systems using Tensor Train. International Journal for Numerical Methods in Engineering, 2022, ⟨10.1002/nme.7067⟩. ⟨hal-03375811v3⟩
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