Combining Krylov subspace methods and identification-based methods for model order reduction

P.J. Heres, D. Deschrijver, W.H.A. Schilders, T. Dhaene

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)
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Abstract

Many different techniques to reduce the dimensions of a model have been proposed in the near past. Krylov subspace methods are relatively cheap, but generate non-optimal models. In this paper a combination of Krylov subspace methods and orthonormal vector fitting (OVF) is proposed. In that way a compact model for a large model can be generated. In the first step, a Krylov subspace method reduces the large model to a model of medium size, then a compact model is derived with OVF as a second step.
Original languageEnglish
Pages (from-to)271-282
JournalInternational Journal of Numerical Modelling : Electronic Networks, Devices and Fields
Volume20
Issue number6
DOIs
Publication statusPublished - 2007

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