論文

査読有り
2018年

Structure-preserving technique in the block SS–Hankel method for solving hermitian generalized eigenvalue problems

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Akira Imakura
  • ,
  • Yasunori Futamura
  • ,
  • Tetsuya Sakurai

10777
開始ページ
600
終了ページ
611
記述言語
英語
掲載種別
研究論文(国際会議プロシーディングス)
DOI
10.1007/978-3-319-78024-5_52
出版者・発行元
Springer Verlag

The block SS–Hankel method is one of the most efficient methods for solving interior generalized eigenvalue problems (GEPs) when only the eigenvalues are required. However, even if the target GEP is Hermitian, the block SS–Hankel method does not always preserve the Hermitian structure. To overcome this issue, in this paper, we propose a structure-preserving technique of the block SS–Hankel method for solving Hermitian GEPs. We also analyse the error bound of the proposed method and show that the proposed method improves the accuracy of the eigenvalues. The numerical results support the results of the analysis.

リンク情報
DOI
https://doi.org/10.1007/978-3-319-78024-5_52
ID情報
  • DOI : 10.1007/978-3-319-78024-5_52
  • ISSN : 1611-3349
  • ISSN : 0302-9743
  • SCOPUS ID : 85044752504

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