Recursive Signal Processing

Recursive Signal Processing is a signal processing methodology in which the current output is determined by both the current and past inputs as well as past outputs, thereby employing feedback to recursively compute subsequent values within the processing sequence.

69

Publications

2.4K

Citations

137

Authors

76

Institutions

Publications per year

2017–2026

3

Authors

137

  1. GR
    Gonzalo R. Arce

    University of Delaware, United States

    2 publications · 62 citations

    2

    h-index

  2. BH
    Barbara Hammer

    Bielefeld University, Germany

    2 publications · 33 citations

    2

    h-index

  3. FD
    Feng Ding

    Jiangnan University, China

    2 publications · 196 citations

    2

    h-index

  4. SH
    S. Haykin

    McMaster University, Canada

    2 publications · 91 citations

    2

    h-index

  5. JA
    J.K. Aggarwal

    The University of Texas at Austin, United States

    2 publications · 42 citations

    2

    h-index

1–5 of 137

Venues

  1. 10

    h-index

  2. Signal Processing

    4 publications · 95 citations

    4

    h-index

  3. IEEE Transactions on Signal Processing

    2 publications · 111 citations

    2

    h-index

  4. IEEE Transactions on Information Theory

    2 publications · 62 citations

    2

    h-index

  5. IEEE Transactions on Circuits and Systems

    2 publications · 133 citations

    2

    h-index

1–5