Subspace-based State Estimation

Subspace-Based State Estimation is a state estimation method that belongs to the class of subspace identification techniques and is distinguished by its use of orthogonal projections of input-output data subspaces to directly extract state sequences without requiring prior parametric model assumptions.

101

Publications

5.4K

Citations

257

Authors

132

Institutions

Publications per year

2017–2026

18

Authors

257

  1. MV
    Michel Verhaegen

    Delft University of Technology, Netherlands

    5 publications · 463 citations

    5

    h-index

  2. BD
    Bart De Moor

    KU Leuven, Belgium

    4 publications · 1K citations

    4

    h-index

  3. PV
    Peter Van Overschee

    KU Leuven, Belgium

    4 publications · 1K citations

    4

    h-index

  4. BH
    Biao Huang

    University of Alberta, Canada

    4 publications · 583 citations

    4

    h-index

  5. NC
    N.L.C. Chui

    Bridge University, South Sudan

    3 publications · 87 citations

    3

    h-index

1–5 of 257

Venues

  1. Automatica

    10 publications · 1.3K citations

    10

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  2. IFAC Proceedings Volumes

    8 publications · 144 citations

    8

    h-index

  3. Signal Processing

    4 publications · 266 citations

    4

    h-index

  4. IEEE Transactions on Signal Processing

    3 publications · 247 citations

    3

    h-index

  5. Industrial & Engineering Chemistry Research

    3 publications · 52 citations

    3

    h-index

1–5