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  2. Nyquist–Shannon sampling theorem - Wikipedia

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

    The term Nyquist Sampling Theorem (capitalized thus) appeared as early as 1959 in a book from his former employer, Bell Labs, [22] and appeared again in 1963, [23] and not capitalized in 1965. [24] It had been called the Shannon Sampling Theorem as early as 1954, [25] but also just the sampling theorem by several other books in the early 1950s.

  3. 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 ...

  4. Sampling (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Sampling_(signal_processing)

    In signal processing, sampling is the reduction of a continuous-time signal to a discrete-time signal. A common example is the conversion of a sound wave to a sequence of "samples". A sample is a value of the signal at a point in time and/or space; this definition differs from the term's usage in statistics, which refers to a set of such values ...

  5. List of examples of Stigler's law - Wikipedia

    en.wikipedia.org/wiki/List_of_examples_of_Stigler...

    Norton's theorem was published in November 1926 by Hans Ferdinand Mayer and independently discovered by Edward Lawry Norton who presented it in an internal Bell Labs technical report, dated November 1926. Nyquist–Shannon sampling theorem. The name Nyquist–Shannon sampling theorem honours Harry Nyquist and Claude Shannon, but the theorem was ...

  6. 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 ...

  7. Multidimensional sampling - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_sampling

    A simple illustration of aliasing can be obtained by studying low-resolution images. A gray-scale image can be interpreted as a function in two-dimensional space. An example of aliasing is shown in the images of brick patterns in Figure 5. The image shows the effects of aliasing when the sampling theorem's condition is not satisfied.