Perturbation Analysis

Perturbation Analysis is a methodological framework within Feature Stability Analysis that systematically introduces controlled variations to input features or model parameters to assess the robustness and sensitivity of a model's output, thereby distinguishing it from other analytical approaches by its focus on deliberate, structured disruptions to evaluate feature invariance.

2.8K

Publications

150.4K

Citations

6K

Authors

1.8K

Institutions

Publications per year

2017–2026

390

Authors

6K

  1. CG
    Christos G. Cassandras

    Boston University, United States

    36 publications · 1.6K citations

    21

    h-index

  2. YW
    Yimin Wei

    Fudan University, China

    18 publications · 492 citations

    17

    h-index

  3. XC
    Xi‐Ren Cao

    Hong Kong University of Science and Technology, Hong Kong SAR China

    21 publications · 992 citations

    17

    h-index

  4. MC
    Michael C. Fu

    University of Maryland, College Park, United States

    20 publications · 665 citations

    15

    h-index

  5. JH
    Jian-Qiang Hu

    Fudan University, China

    14 publications · 466 citations

    13

    h-index

1–5 of 6K

Venues

  1. Journal of Fluid Mechanics

    54 publications · 5.1K citations

    32

    h-index

  2. IEEE Transactions on Automatic Control

    52 publications · 3.6K citations

    31

    h-index

  3. The Journal of Chemical Physics

    59 publications · 3.8K citations

    27

    h-index

  4. IEEE Transactions on Signal Processing

    30 publications · 2.3K citations

    24

    h-index

  5. Physical Review Letters

    PRL · 31 publications · 2.1K citations

    24

    h-index

1–5