Relationship between sound quality and sample rate
The conversion of an analog signal to digital consists of two steps: sampling in time and quantization in amplitude.
Time sampling means that the signal is represented by a series of samples (samples) taken at regular intervals. For example, when we say that the sample rate is 44.1 kHz, this means that the signal is measured 44 100 times in one second.
The main problem in the first stage of converting an analog to digital signal (digitization) is the choice of the sampling frequency of the analog signal. The higher the frequency, the closer the digital signal is to the analog. However, in proportion to the increase in frequency, they increase:
The intensity of the digital data flow and the bandwidth of the interfaces are not unlimited, especially if several channels are recorded / played simultaneously;
The computational load on digital processors and their computing capabilities are also limited;
The amount of memory required to store the digital signal is increased.
Obviously, a compromise is needed. The choice of the sampling frequency affects the frequency range of the received digital sound and the maximum frequency of the analog signal, correctly represented in the digital one. It is believed that a person hears frequencies in the range of 20 to 20,000 Hz. According to the well-known Kotelnikov theorem, in order for an analog signal (continuous in time) to be accurately reconstructed from its samples, the sampling frequency must be at least twice the maximum audio frequency.
An audio frequency equal to half the sampling frequency is called the Nyquist frequency and is the maximum frequency that a given digital system can store and reproduce correctly. Therefore, if the actual analog signal that we are going to convert to digital format contains frequency components from 0 to 20 kHz, then the sampling frequency of that signal must be at least 40 kHz. The most common sample rates today are 44.1 kHz (CD) and 48 kHz (DAT).
