Stationarity Features

Stationarity Features is a time series feature extraction method that characterizes temporal invariance properties by identifying statistical homogeneity in mean, variance, and autocorrelation over time.

31

Publications

1K

Citations

85

Authors

59

Institutions

Publications per year

2017–2026

9

Authors

85

  1. JY
    Jianhua Yang

    China University of Mining and Technology, China

    1 publications · 36 citations

    1

    h-index

  2. ER
    Eduardo Rocón

    Consejo Superior de Investigaciones Científicas, Spain

    1 publications · 17 citations

    1

    h-index

  3. YX
    Yu Xin

    Nanjing University of Aeronautics and Astronautics, China

    1 publications · 15 citations

    1

    h-index

  4. CA
    Celia Anteneodo

    Pontifícia Universidade Católica do Rio de Janeiro, Brazil

    1 publications · 13 citations

    1

    h-index

  5. LC
    Longwei Chen

    China Earthquake Administration, China

    1 publications · 30 citations

    1

    h-index

1–5 of 85

Venues

  1. Journal of Business and Economic Statistics

    JBES · 2 publications · 70 citations

    2

    h-index

  2. IEEE Transactions on Biomedical Engineering

    2 publications · 160 citations

    2

    h-index

  3. Journal of Hydrology

    2 publications · 52 citations

    2

    h-index

  4. Reviews of Geophysics

    1 publications · 84 citations

    1

    h-index

  5. Renewable and Sustainable Energy Reviews

    1 publications · 24 citations

    1

    h-index

1–5