- #1
SuchMuch
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Hi everyone,
The task is to process some 1D data which represents a sum of a useful signal and
a background (I've attached few typical samples).
The data are in fact the amplitudes of the Fourier spectra of some signal.
The goal is to separate a background from useful signal at each frequency.
The common feature in these data is that in each case the amplitude of a background
signal is a smooth function of frequency (n).
The red lines show an approximate boundary between both contributions in each case.
As one can see from the plots, the useful signal exist only at low
frequencies, whereas at higher frequencies only background exist.
Does anyone can give a good advise how to separate backround from such particular type of data?
Accuracy is of great importance, speed of processing is not crusial parameter,
any method (data smoothing, extrapolation, filtering, etc) can be used.
Thanks in advance!
The task is to process some 1D data which represents a sum of a useful signal and
a background (I've attached few typical samples).
The data are in fact the amplitudes of the Fourier spectra of some signal.
The goal is to separate a background from useful signal at each frequency.
The common feature in these data is that in each case the amplitude of a background
signal is a smooth function of frequency (n).
The red lines show an approximate boundary between both contributions in each case.
As one can see from the plots, the useful signal exist only at low
frequencies, whereas at higher frequencies only background exist.
Does anyone can give a good advise how to separate backround from such particular type of data?
Accuracy is of great importance, speed of processing is not crusial parameter,
any method (data smoothing, extrapolation, filtering, etc) can be used.
Thanks in advance!