Residual-based Detection

Residual-Based Detection is a fault detection method that identifies system anomalies by analyzing the residual signal, which represents the discrepancy between the actual system output and the predicted output generated by a nominal model.

90

Publications

6.1K

Citations

268

Authors

138

Institutions

Publications per year

2017–2026

40

Authors

268

  1. SX
    Steven X. Ding

    University of Duisburg-Essen, Germany

    4 publications · 79 citations

    4

    h-index

  2. RD
    R. Doraiswami

    University of New Brunswick, Canada

    3 publications · 70 citations

    3

    h-index

  3. FC
    F.N. Chowdhury

    University of Louisiana at Lafayette, United States

    3 publications · 37 citations

    3

    h-index

  4. DC
    Davide Cozzolino

    University of Naples Federico II, Italy

    3 publications · 483 citations

    3

    h-index

  5. LV
    Luisa Verdoliva

    University of Naples Federico II, Italy

    3 publications · 483 citations

    3

    h-index

1–5 of 268

Venues

  1. IEEE Transactions on Smart Grid

    4 publications · 183 citations

    4

    h-index

  2. IEEE Transactions on Cybernetics

    3 publications · 128 citations

    3

    h-index

  3. 2

    h-index

  4. IET Control Theory and Applications

    2 publications · 49 citations

    2

    h-index

  5. International Journal of Control

    2 publications · 53 citations

    2

    h-index

1–5