publication . Preprint . 2020

Maximum Entropy Snapshot Sampling for Reduced Basis Modelling

Bannenberg, M.W.F.M.; Kasolis, F.; Günther, M.; Clemens, M.;
Open Access English
  • Published: 20 Oct 2020
The so-called maximum entropy snapshot sampling method is employed for reducing two nonlinear circuit models. The maximum entropy snapshot sampling directly reduces the number of snapshots by recursively identifying and selecting the snapshots that strictly increase an estimate of the correlation entropy of the considered systems. Reduced bases are then obtained with the orthogonal-triangular decomposition. In the first case study, the resulting overdetermined systems are solved in the least squares sense. In the second case study, the basis is incorporated in a reduced order multirate scheme, whilst the reduction parameter is estimated through an optimality req...
Persistent Identifiers
free text keywords: Circuit models, entropy, nonlinear model reduction, QR decomposition
Funded by
Reduced Order Modelling, Simulation and Optimization of Coupled systems
  • Funder: European Commission (EC)
  • Project Code: 765374
  • Funding stream: H2020 | MSCA-ITN-EID
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Preprint . 2020
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