Peak Features

Peak Features is a time series feature engineering method that characterizes temporal patterns by identifying and quantifying local maxima in a sequence, distinguished by their focus on amplitude, duration, and recurrence of peaks to capture salient dynamic behaviors in the data.

122

Publications

7K

Citations

465

Authors

237

Institutions

Publications per year

2017–2026

23

Authors

465

  1. NT
    Neepa T. Maitra

    City University of New York, United States

    3 publications · 146 citations

    3

    h-index

  2. WZ
    Wenchao Zhang

    Noble Research Institute, United States

    3 publications · 169 citations

    3

    h-index

  3. MI
    Mohd Ibrahim Shapiai

    University of Technology Malaysia, Malaysia

    2 publications · 57 citations

    2

    h-index

  4. LW
    Lloyd W. Sumner

    Noble Research Institute, United States

    2 publications · 89 citations

    2

    h-index

  5. MM
    Marizan Mubin

    University of Malaya, Malaysia

    2 publications · 57 citations

    2

    h-index

1–5 of 465

Venues

  1. The Journal of Chemical Physics

    13 publications · 732 citations

    12

    h-index

  2. Analytical Chemistry

    8 publications · 839 citations

    8

    h-index

  3. Physical review. B, Condensed matter

    PRB · 6 publications · 769 citations

    6

    h-index

  4. Journal of Chromatographic Science

    JCS · 3 publications · 65 citations

    3

    h-index

  5. Physical Review B

    PRB · 3 publications · 158 citations

    3

    h-index

1–5