Analog to Digital Conversion

The first step in performing an FFT analysis is the actual sampling process, which is illustrated here:

Analog to Digital Conversion

The sampling is an analog, not digital, process and is accomplished with a "sample and hold" circuit. The output of this circuit is a sequence of voltage levels that are fed into an analog to digital converter (ADC). Here the voltage levels are converted into digital words representing each sampled level. The accuracy of the sampled levels depends in part on the number of bits in the digital words. The greater the number of bits, the lower the noise level and the greater the dynamic range will be. Most FFT analyzers use 12-bit words and this produces a dynamic range of about 70 dB (3,100:1). Fourteen bit words can achieve 80 dB (10,000:1) dynamic range.

It can be seen here that the sampling rate determines the highest frequency in the signal that can be encoded. The sampled waveform cannot know anything about what happens in the signal between the sampled times. Claude Shannon, the developer of the branch of mathematics called information theory, determined that to encode all the information in a signal being sampled, the sampling frequency must be at least double the highest frequency present in the signal. This fact is sometimes called the Nyquist criterion.