Nyquist Sampling Theorem

The Nyquist Sampling Theorem is a fundamental principle in signal processing that specifies the minimum sampling rate required to accurately reconstruct a continuous band-limited signal from its discrete samples without aliasing, stating that the sampling frequency must be at least twice the highest frequency present in the signal.

194

Publications

21K

Citations

548

Authors

272

Institutions

Publications per year

2017–2026

60

Variants

Nyquist-shannon Sampling TheoremWhittaker-nyquist-kotelnikov-shannon TheoremWks Theorem

Authors

548

  1. MV
    Martin Vetterli

    École Polytechnique Fédérale de Lausanne, Switzerland

    4 publications · 170 citations

    4

    h-index

  2. AA
    Aamir Anis

    University of Southern California, United States

    3 publications · 358 citations

    3

    h-index

  3. XX
    Xiang‐Gen Xia

    University of Delaware, United States

    3 publications · 203 citations

    3

    h-index

  4. ND
    Nicholas D. Sidiropoulos

    University of Minnesota, United States

    3 publications · 191 citations

    3

    h-index

  5. AG
    Akshay Gadde

    University of Southern California, United States

    3 publications · 358 citations

    3

    h-index

1–5 of 548

Venues

  1. IEEE Transactions on Signal Processing

    11 publications · 760 citations

    11

    h-index

  2. Signal Processing

    7 publications · 229 citations

    7

    h-index

  3. Optics Express

    6 publications · 297 citations

    6

    h-index

  4. arXiv (Cornell University)

    Repository · 6 publications · 142 citations

    5

    h-index

  5. IEEE Signal Processing Magazine

    4 publications · 10.4K citations

    4

    h-index

1–5