Why does the signal become thicker after noise reduction and the dots on both sides diverge?

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I want to apply a voice noise reduction program similar to the one below to my own 1D signal, but I found that after noise reduction, the 1D signal becomes thicker and the points at both ends of the signal become divergent, and I can't find the cause of this phenomenon and how to fix it. Hope to get your help. Have a great day!
the program is that:
my result is as follow:
the red is clean signal, the yellow is signal with noise, and the green is signal after denoisng.
  3 Comments
Mathieu NOE
Mathieu NOE on 19 Sep 2024
at least the two bottom plots from your yellow window seem just signal + white noise , no a reverb effect.
Are you sure you are using the right tool for the task ? there may be other ways to achieve your goal
very simple solution like smoothing (smoothdata.m) , polyfit or spline smoothing , or this (also usefull for 1D signal denoising) :
Yi Ma
Yi Ma on 19 Sep 2024
@Sumukh sure, the 1D signla as follow 2F8.mat, "R” is clean signal, "y" is signal with noise, and "z" is noise. Each column in R, y, and z is a signal.

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Answers (1)

Mathieu NOE
Mathieu NOE on 20 Sep 2024
hello again
you can already get decent results with smoothdata , other smoothing techniques based on splines or NN could also work
this is the 4th y data , processed with the code shown below :
for k = 1:4
figure(k)
ys1 = smoothdata(y(:,k),'sgolay',150);
ys2 = smoothn(y(:,k),'robust');
plot(y(:,k))
hold on
plot(ys1)
plot(ys2)
legend('noisy signal','smoothdata','smoothn')
end
  4 Comments
Yi Ma
Yi Ma on 24 Sep 2024
Edited: Yi Ma on 24 Sep 2024
yes, i have tried it as your method, the result is interesting. as the follows figures, only the second signal is perfect. i will to look at why this happens. This inspires me a lot, thank you very much!

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