Random Fluctuation Modeling

Random Fluctuation Modeling is a stochastic modeling framework that characterizes unpredictable variations in a system or process by isolating and quantifying inherent randomness, distinguishing it from deterministic trends or external influences within fluctuation analysis.

130

Publications

6.2K

Citations

362

Authors

172

Institutions

Publications per year

2017–2026

18

Authors

362

  1. DF
    D.J. Frank

    IBM Research - Thomas J. Watson Research Center, United States

    4 publications · 227 citations

    4

    h-index

  2. HP
    H.‐S. Philip Wong

    Stanford University, United States

    4 publications · 559 citations

    4

    h-index

  3. TH
    Toshiro Hiramoto

    The University of Tokyo, Japan

    3 publications · 225 citations

    3

    h-index

  4. AN
    Akio Nishida

    Mirai Hospital, Japan

    3 publications · 225 citations

    3

    h-index

  5. JV
    Jorge Viñals

    Florida State University, United States

    2 publications · 27 citations

    2

    h-index

1–5 of 362

Venues

  1. 7

    h-index

  2. Physical Review E

    PRE · 4 publications · 142 citations

    4

    h-index

  3. IEEE Electron Device Letters

    3 publications · 82 citations

    3

    h-index

  4. IEEE Transactions on Electron Devices

    3 publications · 643 citations

    3

    h-index

  5. Mathematical Biosciences

    3 publications · 146 citations

    3

    h-index

1–5