# How to get a smooth plot by filtering the sudden variation of the data?

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Sateesh Kandukuri am 11 Mär. 2023
Kommentiert: Sateesh Kandukuri am 11 Mär. 2023
I calculated the numerical derivative of my data as a function of time to get the speed. I got a noisy curve. Then I took the Fourier transform of the velocity data and filtered it to remove the sudden variations and smoothen it. The filtered data is not matching with the unfiltered data. Can anybody help me to solve this issue?
clear;
t = A(:,1);
v = A(:,2);
vfreq=fft(v);
vfreq1=fftshift(vfreq);
vfreq2=vfreq1;
for k=1:485
vfreq2(k)=0;
end
for k=515:size(vfreq1,1)
vfreq2(k)=0;
end
vfreq2=ifftshift(vfreq2);
dvxfilt=ifft(vfreq2);
plot(t/1e-9,dvxfilt);
xlabel('t (ns)')
ylabel('v')
xlim([0 100]);
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### Antworten (1)

Bruno Luong am 11 Mär. 2023
Bearbeitet: Bruno Luong am 11 Mär. 2023
It recovers a big tail part of the signal. Hard to guess what should be the signal at the begining.
x=A(:,1);
A=A(:,2);
B=flip(unwrap(flip(A)*10)/10);
plot(x,A,"g")
hold on
plot(x,B,'r','LineWidth',2)
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Bruno Luong am 11 Mär. 2023
Bearbeitet: Bruno Luong am 11 Mär. 2023
IMO your data are too corrupted to hope to recover reliable. You have to take the idea and push to the limit. I don't have time (and desire) to analyse your data.
There are several post about taking derivative, I recommend you to search and take a look in the archive, for example here
Sateesh Kandukuri am 11 Mär. 2023
@Bruno Luong These fluctuations are mainly due to my system behaviour. We verified the data. The position functions are varying smoothly.

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