Howtosignalprocessing
- What will happen if sampling process should not follow the Nyquist theorem?
- What is Nyquist theorem explain briefly?
- What is the difference between sampling theorem and Nyquist theorem?
- Why is it important to follow Nyquist when sampling?
What will happen if sampling process should not follow the Nyquist theorem?
If the Nyquist theorem is not obeyed, higher frequency information is recorded in too low a sample rate, resulting in aliasing artifacts.
What is Nyquist theorem explain briefly?
The Nyquist theorem specifies that a sinuisoidal function in time or distance can be regenerated with no loss of information as long as it is sampled at a frequency greater than or equal to twice per cycle.
What is the difference between sampling theorem and Nyquist theorem?
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.
Why is it important to follow Nyquist when sampling?
If the signal contains high frequency components, we will need to sample at a higher rate to avoid losing information that is in the signal. In general, to preserve the full information in the signal, it is necessary to sample at twice the maximum frequency of the signal. This is known as the Nyquist rate.
