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

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.

Answer 1

[Voss]

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

[Benjamin]

Got it. Thanks a million!

[Voss]

You're welcome! Any questions, let me know. Otherwise, please "Accept This Answer". Thanks!