Nyquist Theorem formula |
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| \( f_s \;>\; 2 \cdot f_{max} \) | ||
| Symbol | English | Metric |
| \( f_s \) = Sampling Frequency (Rate at which the Frequency is Sam, pled) | \(Hz\) | \(Hz\) |
| \( f_{max} \) = Highest Frequency Present in the Sample | \(Hz\) | \(Hz\) |
Nyquist theorem, abbreviated as \( f_s \), also called Nyquist sampling theorem or Nyquist-Shannon sampling theorem, is used in signal processing that defines the minimum rate at which a continuous signal must be sampled in order to accurately reconstruct it without losing information. According to the theorem, the sampling frequency must be at least twice the highest frequency component present in the signal. This minimum rate is known as the Nyquist rate. If a signal is sampled below this rate, aliasing occurs, meaning different signal components become indistinguishable from each other, causing distortion. The Nyquist theorem is used in digital communications, audio processing, and data conversion systems, as it ensures that analog signals can be faithfully represented and reconstructed in digital form.
This formula states that to accurately reconstruct a continuous signal from its samples without distortion or aliasing, the sampling frequency must be at least twice the highest frequency component of the original signal.
