Reduced rank extrapolation for multi-term Sylvester equations
Abstract
We investigate the acceleration of stationary iterations for multi-term Sylvester equation by means of reduced rank extrapolation (RRE). Theoretical convergence results and implementations are provided for both small and large-scale problems. For the large-scale problems, an inexact non-stationary iteration is discussed, which makes use of low-rank matrix approximations. Numerical experiments illustrate the potential of the RRE acceleration which often leads to a substantial gain in convergence speed and therefore reducing the consumption of storage and computing time.
Fields of Study & Subjects
Statistical and numerical algorithms
Matrix Theory and Algorithms
Model Reduction and Neural Networks
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 13 March 2026
- Document type
- Preprint