Smoothing of noisy data

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Hello everyone, I want to smooth my data, which looks like
It is possible to see a trend, more or less. Using smooth(data)
Do you have any advice to improve it?

Accepted Answer

Image Analyst
Image Analyst on 21 Mar 2020
You forgot to attach your data. But you can try smoothdata(). It looks like it in turn calls movmean(), movmedian(), sgolayfilt(), or whatever smoothing method you want:
Smoothing method, specified as one of the following:
  • 'movmean' — Moving average over each window of A. This method is useful for reducing periodic trends in data.
  • 'movmedian' — Moving median over each window of A. This method is useful for reducing periodic trends in data when outliers are present.
  • 'gaussian' — Gaussian-weighted moving average over each window of A.
  • 'lowess' — Linear regression over each window of A. This method can be computationally expensive, but results in fewer discontinuities.
  • 'loess' — Quadratic regression over each window of A. This method is slightly more computationally expensive than 'lowess'.
  • 'rlowess' — Robust linear regression over each window of A. This method is a more computationally expensive version of the method 'lowess', but it is more robust to outliers.
  • 'rloess' — Robust quadratic regression over each window of A. This method is a more computationally expensive version of the method 'loess', but it is more robust to outliers.
  • 'sgolay' — Savitzky-Golay filter, which smooths according to a quadratic polynomial that is fitted over each window of A. This method can be more effective than other methods when the data varies rapidly.
  5 Comments
Image Analyst
Image Analyst on 22 Mar 2020
Looks like a nice tool. It would be nice if it were somehow available for those of us who prefer the traditional editor instead of the live script editor. Like if it were callable from the command line or on the Apps tab of the tool ribbon.

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