Abstract
A general framework for structure-preserving model reduction by Krylov subspace projection methods is developed. The goal is to preserve any substructures of importance in the matrices L, G, C, B that define the model prescribed by transfer function H (s) = L*(G + sC)-1 B. Many existing structure-preserving model-order reduction methods for linear and second-order dynamical systems can be derived under this general framework. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Li, R. C., & Bai, Z. (2006). Structure-preserving model reduction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3732 LNCS, pp. 323–332). Springer Verlag. https://doi.org/10.1007/11558958_38
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