How to remove data noise through averaging adjacent elements in a data set.

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I am trying to remove noise from my data that includes outliers which are skewing the final result. I'm wondering how I can average two adjacent elements sequentially for a whole data set in order to incorporate outliers more effectively and generate a more streamlined data set. For example, [a b c d e f g ...] it would look like (a+b)/2 and (c+d)/2 and (e+f)/2 ....and so on. I figured I should use a for loop but unsure what that would look like.

Answers (1)

Voss
Voss on 17 Nov 2022
x = 1:10
x = 1×10
1 2 3 4 5 6 7 8 9 10
One way:
xm = movmean(x,2)
xm = 1×10
1.0000 1.5000 2.5000 3.5000 4.5000 5.5000 6.5000 7.5000 8.5000 9.5000
xm = xm(2:2:end)
xm = 1×5
1.5000 3.5000 5.5000 7.5000 9.5000
Another way:
xm = mean(reshape(x,2,[]),1)
xm = 1×5
1.5000 3.5000 5.5000 7.5000 9.5000

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