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Nyquist–Shannon sampling theorem

Sufficiency theorem for reconstructing signals from samples

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Record originEnglish Wikipedia
Text licenseCC BY-SA 4.0
Source revisionSep 9, 2026
Entity authoritySource title only
Source-derived summary

The Nyquist–Shannon sampling theorem, or the sampling theorem, is a theorem in the field of signal processing which serves as a fundamental bridge between continuous-time signals and discrete-time signals. In the case of uniformly spaced (periodic) sampling, it establishes a sufficient condition on the sample rate that permits a discrete sequence of samples to capture all the information from a continuous-time signal of finite bandwidth, such that the original signal can be reconstructed exactly from those samples.

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Editorial reviewA practical starting point whose main value is the path it opens into stronger specialist and primary sources. The current 77-word lead offers orientation but no explicit four-digit date, so chronology should not be assumed. The selected authority fields contribute no independent date. The account is most persuasive where Nyquist, Shannon and sampling can be independently traced.
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Vocabulary and entity names are the principal evidence signals here, because they determine the precision of every later search. The source revision retrieved here is dated Sep 9, 2026.

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This entry incorporates text from Nyquist–Shannon sampling theorem” on English Wikipedia. Contributors are listed in the page history. Text is available under the Creative Commons Attribution-ShareAlike 4.0 License. Selected authority identifiers and statements are retrieved from Wikidata under CC0; their references and qualifiers remain part of the verification path.