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Model Order Reduction of Nonlinear Systems By Interpolating Input-Output Behavior

  • Michael Striebel
  • Joost Rommes
Conference paper
Part of the Mathematics in Industry book series (MATHINDUSTRY, volume 17)

Abstract

In this paper we propose a new approach for model order reduction of parameterized nonlinear systems. Instead of projecting onto the dominant state space, an analog macromodel is constructed for the dominant input-output behavior. This macromodel is suitable for (re)use in analog circuit simulators. The performance of the approach is illustrated for a benchmark nonlinear system.

Keywords

Proper Orthogonal Decomposition Model Order Reduction Lower Dimensional Subspace Nonlinear Circuit Numerical Time Integration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Bergische Universität WuppertalWuppertalGermany
  2. 2.NXP SemiconductorsEindhovenThe Netherlands

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