Cross-Correlation for noise reduction
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Dear All,
I have two signals one is highly noisy (x1) and the other has less noise (x2) where the original signal x is the same. I want to denoise the signal (x2), and the fisrt method comes to my mind is using cross-correlation method, provided that I dont know the original function form and only have these two noisy sequences. However I am not sure how to do this. Accosring to my understanding, the cross correlation returns peaks where these signals are correlated as a fuction of lag and not return a denoised time domain signal. Can I use cross-correlation method to get third time-domain (which should be near or the same of x) signal let say x3 with less noise than x1 and x2?
Your omments are highly appreciated.
t=0:0.001:10;
x=sin(t);
x1=x+0.5*rand(size(x));
x2=x+0.1*rand(size(x));
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Gabriel H Gosselin
2021-12-2
编辑:Gabriel H Gosselin
2021-12-2
Hi, I am facing a similar problem to the one you described in this post where noise is introduced in "Sensor A" by a process measured by "Sensor B". My first thoughts were along the lines of using cross correlation and I found your post.
The ICA method suggested above could be uesd by iteratively comparing its independent components to the "Sensor B" time series, but I think it should be possible tio directly use that time series to denoise the "Sensor A" time series.
May I ask what kind of method you ended up using?
Several aspects of signal processing are still rather new to me. Any pointers would be greatly appreciated!
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