Sparse Signal Representation

Sparse Signal Representation is a signal modeling framework in which a signal is expressed as a linear combination of a few selected basis elements from an overcomplete dictionary, thereby emphasizing parsimony in the representation through minimal non-zero coefficients.

5.3K

Publications

444.4K

Citations

10.6K

Authors

2.2K

Institutions

Publications per year

2017–2026

1.6K

Authors

10.6K

  1. ME
    Michael Elad

    Technion – Israel Institute of Technology, Israel

    70 publications · 28.3K citations

    43

    h-index

  2. RG
    Richard G. Baraniuk

    Rice University, United States

    47 publications · 11.1K citations

    32

    h-index

  3. RG
    Rémi Gribonval

    Institut national de recherche en sciences et technologies du numérique, France

    46 publications · 4.2K citations

    30

    h-index

  4. YC
    Yonina C. Eldar

    Technion – Israel Institute of Technology, Israel

    49 publications · 8.8K citations

    29

    h-index

  5. MB
    Michael B. Wakin

    Colorado School of Mines, United States

    31 publications · 4.4K citations

    25

    h-index

1–5 of 10.6K

Venues

  1. IEEE Transactions on Signal Processing

    336 publications · 64.8K citations

    100

    h-index

  2. IEEE Transactions on Information Theory

    134 publications · 34.7K citations

    68

    h-index

  3. IEEE Transactions on Geoscience and Remote Sensing

    104 publications · 9.6K citations

    54

    h-index

  4. IEEE Signal Processing Letters

    141 publications · 10.1K citations

    50

    h-index

  5. IEEE Transactions on Image Processing

    116 publications · 16K citations

    49

    h-index

1–5