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  2. Nyquist–Shannon sampling theorem - Wikipedia

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

    The Nyquist–Shannon sampling theorem is an essential principle for digital signal processing linking the frequency range of a signal and the sample rate required to avoid a type of distortion called aliasing. The theorem states that the sample rate must be at least twice the bandwidth of the signal to avoid aliasing.

  3. 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 of a given function or signal

  4. Bandwidth (signal processing) - Wikipedia

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

    The Rayleigh bandwidth of a simple radar pulse is defined as the inverse of its duration. For example, a one-microsecond pulse has a Rayleigh bandwidth of one megahertz. [1] The essential bandwidth is defined as the portion of a signal spectrum in the frequency domain which contains most of the energy of the signal. [2]

  5. Downsampling (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Downsampling_(signal...

    Both downsampling and decimation can be synonymous with compression, or they can describe an entire process of bandwidth reduction and sample-rate reduction. [ 1 ] [ 2 ] When the process is performed on a sequence of samples of a signal or a continuous function, it produces an approximation of the sequence that would have been obtained by ...

  6. Oversampling - Wikipedia

    en.wikipedia.org/wiki/Oversampling

    The Nyquist rate is defined as twice the bandwidth of the signal. Oversampling is capable of improving resolution and signal-to-noise ratio, and can be helpful in avoiding aliasing and phase distortion by relaxing anti-aliasing filter performance requirements. A signal is said to be oversampled by a factor of N if it is sampled at N times the ...

  7. Sampling (signal processing) - Wikipedia

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

    Functions of space, time, or any other dimension can be sampled, and similarly in two or more dimensions. For functions that vary with time, let () be a continuous function (or "signal") to be sampled, and let sampling be performed by measuring the value of the continuous function every seconds, which is called the sampling interval or sampling period.

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  9. Normalized frequency (signal processing) - Wikipedia

    en.wikipedia.org/wiki/Normalized_frequency...

    When is normalized with reference to the sampling rate as ′ =, the normalized Nyquist angular frequency is π radians/sample. The following table shows examples of normalized frequency for f = 1 {\displaystyle f=1} kHz , f s = 44100 {\displaystyle f_{s}=44100} samples/second (often denoted by 44.1 kHz ), and 4 normalization conventions: