Interpolation-based Model Reduction

Interpolation-Based Model Reduction is a model reduction method that constructs reduced-order models by enforcing interpolation conditions on the transfer function or system response of the original high-dimensional system at selected sample points in the parameter or frequency domain.

127

Publications

6.9K

Citations

217

Authors

119

Institutions

Publications per year

2017–2026

35

Authors

217

  1. SG
    Serkan Gugercin

    Virginia Tech, United States

    14 publications · 936 citations

    13

    h-index

  2. PB
    Peter Benner

    Max Planck Institute for Dynamics of Complex Technical Systems, Germany

    15 publications · 614 citations

    12

    h-index

  3. CB
    Christopher Beattie

    Virginia Tech, United States

    11 publications · 753 citations

    11

    h-index

  4. KA
    Kyle A. Gallivan

    Florida State University, United States

    6 publications · 441 citations

    6

    h-index

  5. TB
    Tobias Breiten

    University of Graz, Austria

    5 publications · 246 citations

    5

    h-index

1–5 of 217

Venues

  1. IEEE Transactions on Automatic Control

    7 publications · 531 citations

    7

    h-index

  2. SIAM Journal on Scientific Computing

    7 publications · 906 citations

    7

    h-index

  3. IEEE Transactions on Magnetics

    6 publications · 202 citations

    6

    h-index

  4. arXiv (Cornell University)

    Repository · 5 publications · 88 citations

    5

    h-index

  5. Mathematical and Computer Modelling of Dynamical Systems

    MCMDS · 4 publications · 125 citations

    4

    h-index

1–5