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  2. Nyquist–Shannon sampling theorem - Wikipedia

    en.wikipedia.org/wiki/Nyquist–Shannon_sampling...

    The sampling theorem introduces the concept of a sample rate that is sufficient for perfect fidelity for the class of functions that are band-limited to a given bandwidth, such that no actual information is lost in the sampling process. It expresses the sufficient sample rate in terms of the bandwidth for the class of functions.

  3. Whittaker–Shannon interpolation formula - Wikipedia

    en.wikipedia.org/wiki/Whittaker–Shannon...

    The Whittaker–Shannon interpolation formula or sinc interpolation is a method to construct a continuous-time bandlimited function from a sequence of real numbers. The formula dates back to the works of E. Borel in 1898, and E. T. Whittaker in 1915, and was cited from works of J. M. Whittaker in 1935, and in the formulation of the Nyquist–Shannon sampling theorem by Claude Shannon in 1949.

  4. Nonuniform sampling - Wikipedia

    en.wikipedia.org/wiki/Nonuniform_sampling

    Nonuniform sampling is based on Lagrange interpolation and the relationship between itself and the (uniform) sampling theorem. Nonuniform sampling is a generalisation of the Whittaker–Shannon–Kotelnikov (WSK) sampling theorem. The sampling theory of Shannon can be generalized for the case of nonuniform samples, that is, samples not taken ...

  5. Oversampling - Wikipedia

    en.wikipedia.org/wiki/Oversampling

    The sampling theorem states that sampling frequency would have to be greater than 200 Hz. Sampling at four times that rate requires a sampling frequency of 800 Hz. This gives the anti-aliasing filter a transition band of 300 Hz ((f s /2) − B = (800 Hz/2) − 100 Hz = 300 Hz) instead of 0 Hz if the sampling frequency was 200 Hz. Achieving an ...

  6. Oversampling and undersampling in data analysis - Wikipedia

    en.wikipedia.org/wiki/Oversampling_and_under...

    A variety of data re-sampling techniques are implemented in the imbalanced-learn package [1] compatible with the scikit-learn Python library. The re-sampling techniques are implemented in four different categories: undersampling the majority class, oversampling the minority class, combining over and under sampling, and ensembling sampling.

  7. Nyquist rate - Wikipedia

    en.wikipedia.org/wiki/Nyquist_rate

    Fig 1: Typical example of Nyquist frequency and rate. They are rarely equal, because that would require over-sampling by a factor of 2 (i.e. 4 times the bandwidth). In signal processing , the Nyquist rate , named after Harry Nyquist , is a value equal to twice the highest frequency ( bandwidth ) of a given function or signal.