A comparative study of 7 algorithms for model reduction

@article{Gugercin2000ACS,
  title={A comparative study of 7 algorithms for model reduction},
  author={Serkan Gugercin and Athanasios C. Antoulas},
  journal={Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187)},
  year={2000},
  volume={3},
  pages={2367-2372 vol.3}
}
Compares seven model reduction algorithms by applying them to four different dynamical systems. There are four singular value decomposition (SVD) based methods, and three moment matching based methods. The results illustrate that overall, balanced reduction and approximate balanced reduction are the best when we consider whole frequency range. Moment matching methods always lead to higher error norms than SVD based methods due to their local nature; but they are numerically more efficient… CONTINUE READING

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