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Automated Reduced Model Order Selection
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DOI：10.1109/LAWP.2014.2364849.png)
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摘要
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This letter proposes to automate generation of reduced-order models used for accelerated S-parameter computation by applying a posteriori model error estimators. So far, a posteriori error estimators were used in Reduced Basis Method (RBM) and Proper Orthogonal Decomposition (POD) to select frequency points at which basis vectors are generated. This letter shows how a posteriori error estimators can be applied to automatically select the order of the reduced model in second-order Model Order Reduction (MOR) methods. Three different error estimators are investigated and compared in order to arrive at a new MOR scheme that is fast, reliable, and fully automated. The effectiveness of the proposed approach is verified by very high accuracy of the computed scattering parameters (S-parameters) for an example of a waveguide filter over a prescribed frequency band.
Keyword:
a posteriori error estimator
model order reduction
S-parameter computation
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2.8W
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