Iterative refinement for symmetric eigenvalue decomposition II: clustered eigenvalues
Work
Year: 2019
Type: article
Abstract: We are concerned with accurate eigenvalue decomposition of a real symmetric matrix A. In the previous paper (Ogita and Aishima in Jpn J Ind Appl Math 35(3): 1007–1035, 2018), we proposed an efficient ... more
Authors Takeshi Ogita, Kensuke Aishima
Institutions Tokyo Woman's Christian University, Hosei University
Cites: 27
Cited by: 20
Related to: 10
FWCI: 2.307
Citation percentile (by year/subfield): 99.99
Topic: Matrix Theory and Algorithms
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
APC paid (est): $2,890
Funders Japan Society for the Promotion of Science, Japan Society for the Promotion of Science, Core Research for Evolutional Science and Technology
Grant IDS 25790096, 16H03917,