The nyquist shannon sampling theorem is the idea that as long as you capture ‘samples’ of signal (like the air pressure over time that is sound) faster that twice the period of the highest frequency component of the signal, all the information is captured and the aignal can be reproduced exactly (in theory).
maybe think of it like looking through a fence. As long as nothing on the other side of the fence is shorter than the spacing between posts, you can everything on the other side.
note that any file can be encoded as text with something like Base64
This does involve a cutoff point in the “maximum” frequency of a signal. Actual sound contains a much larger frequency spectrum than our audio file formats are designed to handle.
The nyquist shannon sampling theorem is the idea that as long as you capture ‘samples’ of signal (like the air pressure over time that is sound) faster that twice the period of the highest frequency component of the signal, all the information is captured and the aignal can be reproduced exactly (in theory).
maybe think of it like looking through a fence. As long as nothing on the other side of the fence is shorter than the spacing between posts, you can everything on the other side.
note that any file can be encoded as text with something like Base64
This does involve a cutoff point in the “maximum” frequency of a signal. Actual sound contains a much larger frequency spectrum than our audio file formats are designed to handle.
Sure but human hearing tends to cap out at around 24khz so a sample rate of 48khz is going to contain everything that we can hear.
Tends to, key word. Some are outliers in every dimension, including maximum perceptible frequency.
I love the fence analogy.