Adaptive Eigenvalue Algorithms

Adaptive Eigenvalue Algorithms is a class of iterative numerical methods for solving eigenvalue problems that dynamically adjust computational parameters or subspaces based on intermediate estimates to improve convergence rates and accuracy.

91

Publications

3.6K

Citations

188

Authors

109

Institutions

Publications per year

2017–2026

8

Authors

188

  1. YY
    Yidu Yang

    Guizhou Normal University, China

    5 publications · 85 citations

    5

    h-index

  2. AZ
    Aihui Zhou

    Academy of Mathematics and Systems Science, China

    3 publications · 228 citations

    3

    h-index

  3. CC
    Carsten Carstensen

    Humboldt-Universität zu Berlin, Germany

    3 publications · 187 citations

    3

    h-index

  4. JB
    Jacob Benesty

    Institut National de la Recherche Scientifique, Canada

    3 publications · 446 citations

    3

    h-index

  5. CP
    Cengiz Pehlevan

    Harvard University, United States

    2 publications · 50 citations

    2

    h-index

1–5 of 188

Venues

  1. IEEE Transactions on Signal Processing

    8 publications · 459 citations

    8

    h-index

  2. 6

    h-index

  3. arXiv (Cornell University)

    Repository · 4 publications · 106 citations

    4

    h-index

  4. 3

    h-index

  5. IMA Journal of Numerical Analysis

    3 publications · 130 citations

    3

    h-index

1–5