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Adaptive PBDW approach to state estimation: noisy observations; user-defined update spaces. (arXiv:1712.09594v1 [math.NA])
来源于:arXiv
We provide a number of extensions and further interpretations of the
Parameterized-Background Data-Weak (PBDW) formulation, a real-time and in-situ
Data Assimilation (DA) framework for physical systems modeled by parametrized
Partial Differential Equations (PDEs), proposed in [Y Maday, AT Patera, JD
Penn, M Yano, Int J Numer Meth Eng, 102(5), 933-965]. Given $M$ noisy
measurements of the state, PBDW seeks an approximation of the form $u^{\star} =
z^{\star} + \eta^{\star}$, where the \emph{background} $z^{\star}$ belongs to a
$N$-dimensional \emph{background space} informed by a parameterized
mathematical model, and the \emph{update} $\eta^{\star}$ belongs to a
$M$-dimensional \emph{update space} informed by the experimental observations.
The contributions of the present work are threefold: first, we extend the
adaptive formulation proposed in [T Taddei, M2AN, 51(5), 1827-1858] to general
linear observation functionals, to effectively deal with noisy observations;
second, we consider an 查看全文>>