Frequency-domain Classification

Frequency-Domain Classification is a methodological approach within time series classification that transforms time-domain signals into the frequency domain using techniques such as the Fourier Transform, enabling classification based on spectral characteristics rather than temporal patterns.

247

Publications

8.7K

Citations

728

Authors

344

Institutions

Publications per year

2017–2026

102

Authors

728

  1. LA
    Les Atlas

    University of Washington, United States

    3 publications · 61 citations

    3

    h-index

  2. YN
    Yogendra Narayan

    Chandigarh University, India

    3 publications · 96 citations

    3

    h-index

  3. BB
    B. Boashash

    The University of Queensland, Australia

    3 publications · 155 citations

    3

    h-index

  4. MG
    Moeness G. Amin

    Villanova University, United States

    3 publications · 97 citations

    3

    h-index

  5. CD
    C. Doncarli

    École Centrale de Nantes, France

    3 publications · 109 citations

    3

    h-index

1–5 of 728

Venues

  1. Pattern Recognition

    7 publications · 348 citations

    7

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  2. IEEE Signal Processing Letters

    4 publications · 208 citations

    5

    h-index

  3. Sensors

    5 publications · 129 citations

    5

    h-index

  4. Expert Systems with Applications

    5 publications · 186 citations

    5

    h-index

  5. 4

    h-index

1–5