1 ACCEPTED SOLUTION
Accepted Solutions
The NanoEdge AI Studio FFT implementation is very standard, there is nothing particular about it.
It outputs the amplitude (or “intensity�?) of each frequency component of the signal, for each frequency.
On the Y axis is the amplitude, in arbitrary units, and on the X axis is the frequency.
This frequency is expressed as a percentage of the sampling frequency used, “fs�?, which is unknown (the user knows it, but not the Studio).
It always goes from 0 to 0.5 on the x axis, because the frequency range reproduced by the Fourier transform is comprised between 0% and 50% of fs (0 Hz and fs/2 Hz), as is the case for all FFTs.
If users use manual filtering in the Studio, they must input their sampling frequency.
In that case, the FFT plots will show the actual hertz values instead of the fs percentages, as shown below (in this example the sampling frequency is set to 1000 Hz).
The NanoEdge AI Studio FFT implementation is very standard, there is nothing particular about it.
It outputs the amplitude (or “intensity�?) of each frequency component of the signal, for each frequency.
On the Y axis is the amplitude, in arbitrary units, and on the X axis is the frequency.
This frequency is expressed as a percentage of the sampling frequency used, “fs�?, which is unknown (the user knows it, but not the Studio).
It always goes from 0 to 0.5 on the x axis, because the frequency range reproduced by the Fourier transform is comprised between 0% and 50% of fs (0 Hz and fs/2 Hz), as is the case for all FFTs.
If users use manual filtering in the Studio, they must input their sampling frequency.
In that case, the FFT plots will show the actual hertz values instead of the fs percentages, as shown below (in this example the sampling frequency is set to 1000 Hz).
