Fourier Features

Fourier Features is a mathematical transformation technique in time series feature extraction that projects temporal data into a frequency domain representation through sinusoidal basis functions, distinguishing itself by capturing periodic patterns via coefficients derived from discrete Fourier transforms.

209

Publications

15.3K

Citations

655

Authors

274

Institutions

Publications per year

2017–2026

94

Authors

655

  1. RM
    Rangeet Mitra

    Indian Institute of Technology Indore, India

    4 publications · 100 citations

    4

    h-index

  2. SW
    Shiyuan Wang

    Southwest University, China

    4 publications · 113 citations

    4

    h-index

  3. VC
    Vinay Chakravarthi Gogineni

    Norwegian University of Science and Technology, Norway

    3 publications · 65 citations

    3

    h-index

  4. HA
    Haim Avron

    Tel Aviv University, Israel

    3 publications · 193 citations

    3

    h-index

  5. JA
    Johan A. K. Suykens

    KU Leuven, Belgium

    3 publications · 80 citations

    3

    h-index

1–5 of 655

Venues

  1. arXiv (Cornell University)

    Repository · 25 publications · 2K citations

    17

    h-index

  2. Pattern Recognition

    6 publications · 456 citations

    6

    h-index

  3. IEEE Transactions on Image Processing

    4 publications · 517 citations

    4

    h-index

  4. Sensors

    4 publications · 138 citations

    4

    h-index

  5. Applied Optics

    4 publications · 139 citations

    4

    h-index

1–5