Filtering

Filtering is a method in the field of signal and data processing that belongs to the class of estimation techniques designed to extract meaningful information from noisy or incomplete observations by recursively updating the state of a dynamic system based on probabilistic models of its evolution and measurement processes, distinguished from smoothing or prediction by its focus on estimating the current state in real time as new sensor data becomes available.

16K

Publications

999.8K

Citations

42.3K

Authors

6.2K

Institutions

Publications per year

2017–2026

3.8K

Authors

42.3K

  1. ZW
    Zidong Wang

    Brunel University of London, United Kingdom

    166 publications · 15.9K citations

    73

    h-index

  2. PS
    Peng Shi

    The University of Adelaide, Australia

    50 publications · 4.7K citations

    35

    h-index

  3. HD
    Hongli Dong

    Northeast Petroleum University, China

    39 publications · 2.9K citations

    29

    h-index

  4. YS
    Yuriy S. Shmaliy

    Universidad de Guanajuato, Mexico

    41 publications · 2.6K citations

    29

    h-index

  5. HG
    Huijun Gao

    Harbin Institute of Technology, China

    30 publications · 4K citations

    27

    h-index

1–5 of 42.3K

Venues

  1. IEEE Transactions on Signal Processing

    451 publications · 39.8K citations

    101

    h-index

  2. IEEE Transactions on Automatic Control

    373 publications · 46.3K citations

    99

    h-index

  3. Automatica

    135 publications · 14.7K citations

    57

    h-index

  4. 55

    h-index

  5. 49

    h-index

1–5