Recursive Estimation

Recursive Estimation is a state estimation method that belongs to the class of sequential inference techniques, distinguished by its use of prior estimates and incoming measurements to iteratively update the current state in a recursive manner, without requiring the full history of data.

1.1K

Publications

61.5K

Citations

2K

Authors

783

Institutions

Publications per year

2017–2026

162

Authors

2K

  1. ZW
    Zidong Wang

    Brunel University of London, United Kingdom

    15 publications · 783 citations

    14

    h-index

  2. FD
    Feng Ding

    Jiangnan University, China

    16 publications · 835 citations

    12

    h-index

  3. LL
    Lennart Ljung

    Linköping University, Sweden

    11 publications · 1.3K citations

    11

    h-index

  4. PC
    Peter C. Young

    Lancaster University, United Kingdom

    9 publications · 655 citations

    9

    h-index

  5. TK
    T. Kailath

    Stanford University, United States

    8 publications · 894 citations

    8

    h-index

1–5 of 2K

Venues

  1. IEEE Transactions on Automatic Control

    55 publications · 6.2K citations

    31

    h-index

  2. Automatica

    26 publications · 2.8K citations

    21

    h-index

  3. IEEE Transactions on Information Theory

    28 publications · 2.1K citations

    20

    h-index

  4. IEEE Transactions on Signal Processing

    24 publications · 3.6K citations

    17

    h-index

  5. 14

    h-index

1–5