Remove noise from time series data

Hello Matlab community,
I have a time series data from different levels with 30 min interval. I tried to use the medfilt1 to remove outliers and worked at some level.
data2=medfilt1(data1,3)
Here is the plot of data1:
And here is the plot of data2:
However what I want to remove is the red crossed parts of the each level. I marked the purple data as an example. I do not want to make a perfectly smooth data but only to remove fluctuations exist at some points.
I wanted to apply 3 sigma method as an option and integrated the code of Adam Danz' code as below but I should have done something missing.
m = mean(data2);
sd = std(data2);
outliers = false(size(data2));
outliers(data2 < m-sd*3) = true;
outliers(data2 > m+sd*3) = true;
figure
t = 1:length(data2);
plot(t, data2, 'b.')
hold on
plot(t(outliers), d(outliers), 'ro')
rh = refline(0,m);
set(rh, 'color', 'm')
rh2 = refline(0,m+sd*3);
rh3 = refline(0,m-sd*3);
set([rh2,rh3], 'color', 'm', 'linestyle', '--')
legend('data', 'outliers', 'mean', '3rd sd')
All I want to do is to filter the fluctiations for each level but I really get confused about what I am doing.
I will glad to hear your suggestions.
Best,
Ezgi

 Accepted Answer

Star Strider
Star Strider on 22 Jun 2022
The sgolayfilt function might be a better option.
Try something like this —
FrameLen = 201;
DataFilt = sgolayfilt(data1, 3, FrameLen);
figure
plot(t, DataFilt)
grid
Experiment with various values of ‘FrameLen’ to get the result you want.
.

4 Comments

Thank you, it was a good alternative.
I will be happy to hear if there is another option to smooth only the outlier data by filtering but not the whole dataset.
My choice would be the filloutliers funciton. It will work on matrix columns, and works here. You will have to choose the appropriate options to get the desired result.
One approach that seems to work for me:
DataFilt = filloutliers(data1, 'center','movmedian', 250);
figure
subplot(2,1,1)
plot(data1)
grid
subplot(2,1,2)
plot(DataFilt)
grid
See the documentation for details, and other options to experiment with (there are several).
.
Thank you for your support, it was very helpful.
As always, my pleasure!

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R2021a

Asked:

on 22 Jun 2022

Commented:

on 22 Jun 2022

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