Loewner

The Loewner framework and transfer functions of singular/rectangular systems. A connection is established between the Loewner framework for model reduction and the generalized inverses of singular and rectangular matrices. In this context both the Moore-Penrose and the Drazin inverses are involved. As a consequence this approach yields transfer functions for singular and rectangular systems. Thus the Loewner framework constitutes a natural and direct way for constructing models from measured input/output data.

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References in zbMATH (referenced in 51 articles )

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  1. Rapisarda, P.; Antoulas, A. C.: A bilinear differential forms approach to parametric structured state-space modelling (2016)
  2. Rapisarda, P.; Antoulas, A. C.: Reprint of “A bilinear differential forms approach to parametric structured state-space modelling” (2016)
  3. Schulze, Philipp; Unger, Benjamin: Data-driven interpolation of dynamical systems with delay (2016)
  4. Benner, Peter; Gugercin, Serkan; Willcox, Karen: A survey of projection-based model reduction methods for parametric dynamical systems (2015)
  5. Drmač, Z.; Gugercin, S.; Beattie, C.: Vector fitting for matrix-valued rational approximation (2015)
  6. Drmač, Z.; Gugercin, S.; Beattie, C.: Quadrature-based vector fitting for discretized (\mathcalH_2) approximation (2015)
  7. Rapisarda, P.; Antoulas, A. C.: Bilinear differential forms and the Loewner framework for rational interpolation (2015)
  8. Son, Nguyen Thanh; Stykel, Tatjana: Model order reduction of parameterized circuit equations based on interpolation (2015)
  9. Ionita, A. C.; Antoulas, A. C.: Data-driven parametrized model reduction in the Loewner framework (2014)
  10. Ionita, Antonio C.; Antoulas, Athanasios C.: Case study: Parametrized reduction using reduced-basis and the Loewner framework (2014)
  11. Sootla, Aivar; Sou, Kin Cheong; Rantzer, Anders: Parametrized model reduction based on semidefinite programming (2013)