Structural Identifiability

Structural Identifiability is a formal property of a mathematical model that determines whether its parameters can be uniquely inferred from observed input-output data under ideal conditions of noise-free and continuous measurements, given the model's assumed system structure.

218

Publications

13.8K

Citations

423

Authors

262

Institutions

Publications per year

2017–2026

65

Authors

423

  1. MJ
    Michael J. Chappell

    University of Warwick, United Kingdom

    15 publications · 629 citations

    14

    h-index

  2. ND
    Neil D. Evans

    University of Warwick, United Kingdom

    12 publications · 418 citations

    12

    h-index

  3. AF
    Alejandro F. Villaverde

    Universidade de Vigo, Spain

    10 publications · 682 citations

    10

    h-index

  4. JR
    Julio R. Banga

    Consejo Superior de Investigaciones Científicas, Spain

    9 publications · 1.1K citations

    9

    h-index

  5. KG
    K.R. Godfrey

    University of Warwick, United Kingdom

    9 publications · 304 citations

    9

    h-index

1–5 of 423

Venues

  1. Mathematical Biosciences

    19 publications · 759 citations

    17

    h-index

  2. IEEE Transactions on Automatic Control

    15 publications · 551 citations

    13

    h-index

  3. Bioinformatics

    8 publications · 2.3K citations

    8

    h-index

  4. Automatica

    7 publications · 248 citations

    7

    h-index

  5. PLoS ONE

    5 publications · 644 citations

    5

    h-index

1–5