Nonlinear Identifiability

Nonlinear Identifiability is the property of a nonlinear model structure that determines whether its parameters can be uniquely inferred from observed input-output data under ideal conditions of noise-free and persistently excited inputs, distinguishing it from linear or structurally identifiable systems by its dependence on nonlinear parametrization and system dynamics.

173

Publications

10.8K

Citations

351

Authors

195

Institutions

Publications per year

2017–2026

38

Authors

351

  1. LD
    Lilianne Denis-Vidal

    Université de Technologie de Compiègne, France

    7 publications · 230 citations

    7

    h-index

  2. MP
    Maria Pia Saccomani

    University of Padua, Italy

    7 publications · 1.2K citations

    7

    h-index

  3. SA
    S. Audoly

    University of Cagliari, Italy

    6 publications · 1.1K citations

    6

    h-index

  4. MJ
    Michael J. Chappell

    University of Warwick, United Kingdom

    6 publications · 486 citations

    6

    h-index

  5. GB
    G. Bellu

    University of Padua, Italy

    6 publications · 917 citations

    6

    h-index

1–5 of 351

Venues

  1. Automatica

    13 publications · 1.4K citations

    12

    h-index

  2. IEEE Transactions on Automatic Control

    14 publications · 700 citations

    11

    h-index

  3. Mathematical Biosciences

    8 publications · 769 citations

    8

    h-index

  4. IFAC Proceedings Volumes

    7 publications · 87 citations

    7

    h-index

  5. International Journal of Non-Linear Mechanics

    3 publications · 115 citations

    3

    h-index

1–5