What does the Nyquist Theorem state about sound frequency sampling?

The Nyquist Theorem is a fundamental principle in digital signal processing that relates to how sound frequencies should be sampled to accurately reproduce the original signal. According to the theorem, in order to properly reconstruct a sound wave, it must be sampled at a rate that is at least twice the highest frequency present in that sound wave. This standard ensures that the digital representation contains sufficient information to capture the nuances of the audio without introducing artifacts such as aliasing.

Sampling at this minimum rate allows for the faithful reproduction of the original sound. If the sampling rate is below this threshold, it can lead to a loss of important audio information, making the playback sound distorted or incorrect.

The other options do not accurately reflect the requirements set by the Nyquist Theorem. Sampling ten times is not necessary and can actually lead to redundancy, while simply recording each cycle once does not guarantee the fidelity needed for accurate sound reproduction. Moreover, the notion that frequency needs no specific sampling rate contradicts the theorem’s principle that specific sampling rates are crucial for accurate sound representation. Overall, the theorem emphasizes the importance of sampling at least twice the highest frequency to ensure precise audio fidelity.