Joint State-parameter Estimation

Joint State-Parameter Estimation is a data assimilation method that simultaneously infers the evolving state variables and unknown or uncertain model parameters of a dynamical system by optimally combining observational data with a numerical model, distinguishing itself from sequential or decoupled estimation approaches through its integrated treatment of state and parameter uncertainties within a unified statistical framework.

209

Publications

12.4K

Citations

552

Authors

297

Institutions

Publications per year

2017–2026

73

Authors

552

  1. FD
    Feng Ding

    Jiangnan University, China

    11 publications · 968 citations

    11

    h-index

  2. TH
    Tasawar Hayat

    Quaid-i-Azam University, Pakistan

    7 publications · 397 citations

    7

    h-index

  3. PM
    Philippe Moireau

    École Polytechnique, France

    5 publications · 290 citations

    5

    h-index

  4. IP
    Inés P. Mariño

    Universidad Rey Juan Carlos, Spain

    4 publications · 85 citations

    4

    h-index

  5. IH
    Ibrahim Hoteit

    King Abdullah University of Science and Technology, Saudi Arabia

    4 publications · 260 citations

    4

    h-index

1–5 of 552

Venues

  1. Automatica

    9 publications · 436 citations

    9

    h-index

  2. Mechanical Systems and Signal Processing

    MSSP · 8 publications · 423 citations

    8

    h-index

  3. IEEE Transactions on Power Systems

    6 publications · 935 citations

    6

    h-index

  4. Advances in Water Resources

    6 publications · 1.2K citations

    6

    h-index

  5. Monthly Weather Review

    5 publications · 209 citations

    5

    h-index

1–5