Matrix Eigenvalue Problems

Matrix Eigenvalue Problems is a mathematical framework within linear algebra that specifically involves determining scalar values and corresponding vectors for which a square matrix acting on a vector yields a scaled version of that vector, distinguishing it from general matrix equations by focusing on eigenstructures inherent in linear transformations.

2.3K

Publications

167K

Citations

3.2K

Authors

1.2K

Institutions

Publications per year

2017–2026

201

Authors

3.2K

  1. YS
    Yousef Saad

    University of Minnesota, United States

    20 publications · 1.5K citations

    16

    h-index

  2. JD
    Jack Dongarra

    University of Tennessee at Knoxville, United States

    19 publications · 813 citations

    16

    h-index

  3. GH
    Gene H. Golub

    Stanford University, United States

    16 publications · 2.3K citations

    15

    h-index

  4. GD
    Guang‐Ren Duan

    Harbin Institute of Technology, China

    18 publications · 1.3K citations

    15

    h-index

  5. KM
    Karl Meerbergen

    KU Leuven, Belgium

    17 publications · 2.1K citations

    14

    h-index

1–5 of 3.2K

Venues

  1. SIAM Journal on Matrix Analysis and Applications

    147 publications · 13.8K citations

    50

    h-index

  2. Linear Algebra and its Applications

    169 publications · 8.1K citations

    48

    h-index

  3. SIAM Journal on Numerical Analysis

    47 publications · 4.5K citations

    30

    h-index

  4. SIAM Journal on Scientific Computing

    50 publications · 2.3K citations

    28

    h-index

  5. Mathematics of Computation

    MCOM · 42 publications · 13.2K citations

    26

    h-index

1–5