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- W2022151828 abstract "Standard model order reduction techniques attempt to build reduced order models of large scale systems with similar input–output behavior over a wide range of input frequencies as the full system models. The method known as the dominant pole algorithm has previously been successfully used in combination with model order reduction techniques to approximate standard linear time-invariant dynamical systems and second order dynamical systems as well as nonlinear time-delay systems. In this paper, we show that the dominant pole algorithm can be adapted for parametric systems where these parameters usually have physical meaning. There are two approaches for finding dominant poles. These algorithms are illustrated by the second order numerical examples." @default.
- W2022151828 created "2016-06-24" @default.
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- W2022151828 date "2014-03-01" @default.
- W2022151828 modified "2023-09-29" @default.
- W2022151828 title "Parametric dominant pole algorithm for parametric model order reduction" @default.
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- W2022151828 doi "https://doi.org/10.1016/j.cam.2013.09.012" @default.
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