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  2. Essential principle for digital signal processing

    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.
    en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem
    en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem
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    Nyquist–Shannon sampling theorem - Wikipedia

    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 … See more

    Sampling is a process of converting a signal (for example, a function of continuous time or space) into a sequence of values (a function … See more

    When there is no overlap of the copies (also known as "images") of $${\displaystyle X(f)}$$, the $${\displaystyle k=0}$$ term of Eq.1 can be recovered by the … See more

    The sampling theorem is usually formulated for functions of a single variable. Consequently, the theorem is directly applicable to time-dependent signals and is normally formulated in that context. However, the sampling theorem can be extended in … See more

    The sampling theory of Shannon can be generalized for the case of nonuniform sampling, that is, samples not taken equally spaced in time. The Shannon sampling theory for … See more

    When $${\displaystyle x(t)}$$ is a function with a Fourier transform $${\displaystyle X(f)}$$:
    $${\displaystyle X(f)\ \triangleq \ \int _{-\infty }^{\infty }x(t)\ e^{-i2\pi ft}\ {\rm {d}}t,}$$
    Then the samples, See more

    Poisson shows that the Fourier series in Eq.1 produces the periodic summation of $${\displaystyle X(f)}$$, regardless of $${\displaystyle f_{s}}$$ See more

    As discussed by Shannon:
    A similar result is true if the band does not start at zero frequency but at some higher value, and can be proved by a linear translation (corresponding physically to single-sideband modulation) of the zero-frequency case. In … See more

     
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  5. Nyquist Sampling Theorem - Statement, Working, …

    Feb 27, 2024 · Nyquist Sampling Theorem states that to reconstruct a continuous analog signal from its sampled version accurately, the sampling rate must be at least twice the highest frequency present in the signal.

  6. What is the Nyquist theorem? - TechTarget

    The Nyquist theorem is also known as the sampling theorem. It is the principle to accurately reproduce a pure sine wave measurement, or sample, rate, which must be at least twice its frequency. The Nyquist theorem underpins all analog …

  7. Nyquist frequency - Wikipedia

  8. The Nyquist–Shannon Theorem: Understanding Sampled Systems

  9. Nyquist Theorem - an overview | ScienceDirect Topics

  10. 10.2: Sampling Theorem - Engineering LibreTexts

    May 22, 2022 · The Nyquist-Shannon Sampling Theorem states that a signal bandlimited to \(\left(-\pi / T_{s}, \pi / T_{s}\right)\) can be reconstructed exactly from its samples with sampling period \(T_s\).

  11. Nyquist Sampling Theorem - Fiveable

  12. Nyquist Criteria : Calculation, Applications & Its …

    Feb 7, 2024 · This Criteria, also known as the Nyquist-Shannon Sampling Theorem, provides a fundamental guideline for determining the minimum sampling rate required to faithfully reconstruct a continuous-time signal in its …

  13. Nyquist | Analog Devices

  14. Acquiring an Analog Signal: Bandwidth, Nyquist Sampling …

  15. Nyquist-Shannon Sampling Theorem - Fiveable

  16. Nyquist Sampling Theorem - (Approximation Theory) - Vocab, …

  17. What is the Nyquist Frequency? - Definition from Techopedia

  18. Nyquist Frequency - (Signal Processing) - Vocab, Definition

  19. Nyquist Frequency - an overview | ScienceDirect Topics

  20. Nyquist Sampling Theorem - (Optical Computing) - Vocab, …

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