Nyquist and Shannon's Sampling Theorems
- Updated2025-07-08
- 3 minute(s) read
The Nyquist theorem concerns digital sampling of a continuous time analog waveform, while Shannon’s Sampling theorem concerns the creation of a continuous time analog waveform from digital, discrete samples.
The 5 MHz frequency aliases back in the passband, falsely appearing as a 1 MHz sine wave.
In this case, the high–frequency sine wave is the desired signal, but was severely undersampled by only being generated by a 6 MS/s DAC; the actual resulting waveform is a 1 MHz signal.
In systems where you want to generate accurate signals using sampled data, the sampling rate must be set high enough to prevent aliasing.
Sample Rate and Shannon's Sampling Theorem
When developing your application, you must keep in mind the sample rates to allow your digital TRM Sample Rate to match Shannon's Sampling Theorem.
According to Shannon’s Sampling theorem, a digital waveform must be updated at least twice as fast as the bandwidth of the signal to be accurately generated. Ideally, a sample rate many times greater than the frequency of the signal produces accurate waveforms. A higher sample rate also captures more waveform details. The following figure illustrates a 1 MHz sine wave generated by a sampled 2 MS/s DAC and a 20 MS/s DAC. The faster DAC generates 20 points per cycle of the expected signal compared with 2 points per cycle with the slower DAC. In this example, the higher sample rate more accurately defines the waveform shape.