Nyquist sampling theorem. It states that the sample rate f s must be greater than twice the highest frequency component of interest in the measured signal. See full list on allaboutcircuits. May 31, 2022 · The Nyquist theorem is also known as the sampling theorem. . com Learn how to turn analog signals into digital signals using the sampling theorem, which states that a bandlimited signal can be reconstructed from its samples if the sampling rate is greater than twice the bandwidth. What Is the Nyquist Theorem? The Nyquist theorem, also known as the Nyquist–Shannon sampling theorem, defines the conditions under which a continuous-time signal can be sampled and perfectly reconstructed from its samples, without losing any information. The theorem states that the sample rate must be at least twice the bandwidth of the signal to avoid aliasing. See examples, proofs, and applications of the theorem and its extensions. Jul 23, 2025 · The Nyquist Sampling Theorem explains the relationship between the sample rate and the frequency of the measured signal. May 30, 2025 · The Nyquist Sampling Theorem explains the relationship between the sample rate and the frequency of the measured signal. It is the principle to accurately reproduce a pure sine wave measurement, or sample, rate, which must be at least twice its frequency. It is used to suggest that the sampling rate must be twice the highest frequency in the signal. 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. xwovc nykm netpd rsb jjxhjd snqer ivji zmp hwx weij