Model Identifiability

Model Identifiability is the property of a mathematical model, within the context of dynamical systems and parameter estimation, that determines whether the model's unknown parameters can be uniquely inferred from observed input-output data under ideal noise-free and error-free measurement conditions.

2.4K

Publications

169.6K

Citations

4K

Authors

1.4K

Institutions

Publications per year

2017–2026

417

Authors

4K

  1. LL
    Lennart Ljung

    Linköping University, Sweden

    47 publications · 6.1K citations

    29

    h-index

  2. FD
    Feng Ding

    Jiangnan University, China

    35 publications · 3.4K citations

    24

    h-index

  3. PM
    Paul M.J. Van den Hof

    Delft University of Technology, Netherlands

    25 publications · 1K citations

    16

    h-index

  4. TS
    Torsten Söderström

    Uppsala University, Sweden

    20 publications · 1.2K citations

    16

    h-index

  5. JR
    Julio R. Banga

    Consejo Superior de Investigaciones Científicas, Spain

    17 publications · 1.8K citations

    16

    h-index

1–5 of 4K

Venues

  1. Automatica

    208 publications · 26.9K citations

    66

    h-index

  2. IEEE Transactions on Automatic Control

    111 publications · 7.4K citations

    42

    h-index

  3. Econometrica

    40 publications · 6.5K citations

    32

    h-index

  4. IFAC Proceedings Volumes

    153 publications · 4.5K citations

    32

    h-index

  5. Mathematical Biosciences

    40 publications · 2.5K citations

    27

    h-index

1–5