Numerical Identifiability

Numerical Identifiability is the property of a mathematical model whereby unique parameter values can be consistently estimated from observed data under numerical computation, distinguishing it from structural identifiability by accounting for practical limitations such as parameter sensitivity, numerical precision, and optimization convergence.

158

Publications

10.6K

Citations

377

Authors

227

Institutions

Publications per year

2017–2026

40

Authors

377

  1. ND
    Nicholas D. Sidiropoulos

    University of Minnesota, United States

    5 publications · 335 citations

    5

    h-index

  2. MP
    Maria Pia Saccomani

    University of Padua, Italy

    4 publications · 545 citations

    4

    h-index

  3. CC
    Claudio Cobelli

    University of Padua, Italy

    4 publications · 176 citations

    4

    h-index

  4. JS
    J.D. Stigter

    Wageningen University & Research, Netherlands

    4 publications · 342 citations

    4

    h-index

  5. LD
    Lilianne Denis-Vidal

    Université de Technologie de Compiègne, France

    4 publications · 120 citations

    4

    h-index

1–5 of 377

Venues

  1. Mathematical Biosciences

    9 publications · 941 citations

    9

    h-index

  2. Automatica

    7 publications · 818 citations

    7

    h-index

  3. IFAC Proceedings Volumes

    6 publications · 122 citations

    6

    h-index

  4. IEEE Transactions on Signal Processing

    5 publications · 703 citations

    5

    h-index

  5. SIAM Journal on Control and Optimization

    4 publications · 90 citations

    4

    h-index

1–5