Howtosignalprocessing
- How do you choose a sampling rate based on frequency?
- How do you choose a sampling frequency in FFT?
- What should be the sampling frequency?
- What is spectral leakage and how it can be reduced?
How do you choose a sampling rate based on frequency?
The Nyquist theorem – choosing the right sample rate
The Nyquist theorem is part of the fundamentals of signal conditioning. Based on that, you must choose the sample rate at least twice as high as the maximum frequency in the signal.
How do you choose a sampling frequency in FFT?
The frequency resolution is equal to the sampling frequency divided by FFT size. For example, an FFT of size 256 of a signal sampled at 8000Hz will have a frequency resolution of 31.25Hz. If the signal is a sine wave of 110 Hz, the ideal FFT would show a sharp peak at 110Hz.
What should be the sampling frequency?
The sampling frequency or sampling rate, fs, is the average number of samples obtained in one second, thus fs = 1/T. Its unit is sample per second or hertz e.g. 48 kHz is 48,000 samples per second.
What is spectral leakage and how it can be reduced?
--> This phenomenon of leaking energy from peak value to other samples is called Spectral leakage. --> This reduction in energy from main lobe is called scalloping loss. Spectral leakage cannot be eliminated but it can be reduced by using proper windowing technique before applying FFT. Cite.
