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  2. 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 ...

  3. Non-uniform discrete Fourier transform - Wikipedia

    en.wikipedia.org/wiki/Non-uniform_discrete...

    It has important applications in signal processing, [1] magnetic resonance imaging, [2] and the numerical solution of partial differential equations. [3] As a generalized approach for nonuniform sampling, the NUDFT allows one to obtain frequency domain information of a finite length signal at any frequency. One of the reasons to adopt the NUDFT ...

  4. 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.

  5. Nyquist frequency - Wikipedia

    en.wikipedia.org/wiki/Nyquist_frequency

    In this example, f s is the sampling rate, and 0.5 cycle/sample × f s is the corresponding Nyquist frequency. The black dot plotted at 0.6 f s represents the amplitude and frequency of a sinusoidal function whose frequency is 60% of the sample rate. The other three dots indicate the frequencies and amplitudes of three other sinusoids that ...

  6. Downsampling (signal processing) - Wikipedia

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

    Sampling rate conversion systems are used to change the sampling rate of a signal. The process of sampling rate decrease is called decimation, and the process of sampling rate increase is called interpolation. T. Schilcher. RF applications in digital signal processing//" Digital signal processing".

  7. Compressed sensing - Wikipedia

    en.wikipedia.org/wiki/Compressed_sensing

    An early breakthrough in signal processing was the Nyquist–Shannon sampling theorem. It states that if a real signal's highest frequency is less than half of the sampling rate, then the signal can be reconstructed perfectly by means of sinc interpolation. The main idea is that with prior knowledge about constraints on the signal's frequencies ...

  8. Nonuniform sampling - Wikipedia

    en.wikipedia.org/wiki/Nonuniform_sampling

    The sampling theory of Shannon can be generalized for the case of nonuniform samples, that is, samples not taken equally spaced in time. The Shannon sampling theory for non-uniform sampling states that a band-limited signal can be perfectly reconstructed from its samples if the average sampling rate satisfies the Nyquist condition. [1]

  9. Sinc function - Wikipedia

    en.wikipedia.org/wiki/Sinc_function

    The sinc function as audio, at 2000 Hz (±1.5 seconds around zero) In mathematics, the historical unnormalized sinc function is defined for x ≠ 0 by ⁡ = ⁡.. Alternatively, the unnormalized sinc function is often called the sampling function, indicated as Sa(x).