Parametric Interpolation Model Order Reduction on Grassmann Manifolds by Parallelization
Based on Riemannian geometry of Grassmann manifolds and discrete Laguerre polynomials, we propose a parametric interpolation parallel MOR method for discrete-time parametric systems. First, a block discrete Fourier transform-based (BDFT) parallel strategy is presented to construct the local basis matrices, which achieves two level acceleration by parallelization. Further, using the retractions and vector transports on Grassmann manifolds, the basis matrix for a new parameter is obtained by interpolating the local bases on the tangent spaces at the different reference points. Finally, a numerical example is used to demonstrate the efficiency of our method.
Authors
- Peter Benner (ORCID: https://orcid.org/0000-0003-3362-4103)
- Zhen Li (ORCID: https://orcid.org/0000-0001-6433-8287)
- Kang-Li Xu (ORCID: https://orcid.org/0000-0002-5623-9956)
Institutions
- Xi'an University of Science and Technology (CN)
- Max Planck Institute for Dynamics of Complex Technical Systems (DE)
- Xi'an Jiaotong University (CN)
Publication Details
- Journal
- IEEE Transactions on Circuits & Systems II Express Briefs
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1109/tcsii.2024.3460171
- Citations
- 5
- Primary Topic
- Model Reduction and Neural Networks
- Type
- article
- Field-Weighted Citation Impact
- 1.41
Funders
- National Natural Science Foundation of China