How to fit/scale a big data set into a smaller one?
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my problem is pretty similiar to this one:
except that I dont have a repeating signal.
My problems is rather looking like this one:
DataSet 1 is the blue plot, defined by 65 X and Y values. DataSet 2 is the yellow one, defined by 3 values. Now my goal is to move, turn, scale etc. the blue data points in a way, so they fit the yellow points in the best possible way. Only limitations are a intersection with zero and the ratio between the blue data must stay equal. I tried several approaches with least square error or lsqcurvefit but the problem is always the difference in the number of values between the 2 data sets. A 9th degree polynomial fit of the blue data comes pretty close to what it looks like.
I also thought of the optimization toolbox, but I am failing to use it in the right way.