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The 26 pages that link to Nyquist–Shannon sampling theorem, each with the reason it gives.

• Digital audioRelated: It explains why sample rates must exceed twice the highest frequency being represented.

• Analog-to-digital converterRelated: It sets the minimum sampling rate needed to avoid losing recoverable signal frequencies.

• BandwidthRelated: It connects a signal’s highest frequency to the sampling rate needed to preserve it.

• Digital imageRelated: It explains when spatial sampling can preserve image detail without aliasing.

• Digital signal processingRelated: It explains the sampling-rate limit for avoiding aliasing during digitization.

• Spatial resolutionRelated: It sets a sampling condition for representing detail, but does not remove optical blur.

• Sampling theoremBroader topic: This is the standard form of the sampling theorem, with its precise rate condition.

• AliasingRelated: Its sampling-rate limit identifies when frequency aliasing can occur.

• Digital signalRelated: It identifies when sampling can preserve an analog signal's information without aliasing.

• Image resolutionRelated: It sets a sampling-rate condition for representing spatial detail without aliasing.

• Optical resolutionRelated: A sensor must sample the optical image finely enough to preserve its detail.

• Display resolutionRelated: It explains why pixel spacing limits the spatial detail a sampled image can represent.

• Analog signalRelated: It establishes conditions for accurately digitizing analog signals.

• Spectral resolutionRelated: It constrains how finely a resolved spectrum must be sampled digitally.

• Digital communicationRelated: It explains when continuous signals can be represented digitally without losing their band-limited content.

• Shannon–Hartley theoremCompared with: It limits signal representation by sampling rate, unlike this theorem's limit on reliable data rate.

• Software-defined radioRelated: It sets a fundamental sampling constraint for digitizing radio signals.

• Sound recording and reproductionRelated: It gives the minimum sampling rate needed to preserve a signal’s frequency range.

• A Mathematical Theory of CommunicationRelated: Earlier work on signal transmission supplied engineering context for Shannon’s communication theory.

• Harry NyquistBroader topic: It gives the precise reconstruction condition associated with Nyquist’s sampling work.

• Poisson summation formulaCompared with: Both connect sampling and frequency structure, but this formula relates lattice sums rather than reconstructing signals.

• ModemRelated: Digital receivers sample incoming waveforms to estimate the transmitted symbols.

• Ralph HartleyRelated: Hartley worked in the same communications research tradition that shaped sampling theory.

• Rectangular functionRelated: Rectangular pulse spectra illustrate why abrupt time limits create broad frequency content.

• High resolutionRelated: It sets a sampling limit on the spatial frequencies an image can represent.

• Wagon-wheel effectRelated: Its sampling limit helps explain why motion sampled too slowly can acquire a false direction.