Create a moving average

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Dirk
Dirk on 28 Jun 2013
Edited: Adam Danz on 19 Sep 2021
Hi There, How can I calculate a moving average for a column of data. For instance i want to average the 50 points either side of each data point in my column. Thanks

Accepted Answer

Andrei Bobrov
Andrei Bobrov on 28 Jun 2013
A - your data
L = filter(ones(101,1)/101,1,[A(:) zeros(50,1)]);
out = L(51:end);

More Answers (5)

Image Analyst
Image Analyst on 28 Jun 2013
Edited: Image Analyst on 28 Jun 2013
For a 1D column vector:
movingAverage = conv(yourSignal, ones(101,1)/101, 'same');
For a 2D array of columns:
movingAverage = conv2(yourSignal, ones(101,1)/101, 'same');
If you don't want the central pixel to be included in the average and have ONLY the 50 on either side, use
kernel = ones(101,1)/100;
kernel(51) = 0;
movingAverage = conv(yourSignal, kernel, 'same');
Same for a 2D matrix except use conv2 instead of conv. conv() and conv2() are highly optimized and very fast.
  4 Comments
Nuchto
Nuchto on 30 Nov 2017
So you could use ones(101,1) first, and onces it is convolved you can divide by 101?

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Grzegorz Knor
Grzegorz Knor on 7 Apr 2017
Edited: Adam Danz on 19 Sep 2021
From MATLAB R2016a there is a function movmean which does not require additional toolboxes.
  1 Comment
Image Analyst
Image Analyst on 7 Apr 2017
True, and it offers some edge handling options ('shrink', 'discard', 'fill') that conv2() does not have.
conv2() also does not require any toolboxes because it's in base MATLAB.

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Marc
Marc on 28 Jun 2013
If you have the financial toolbox, doc movavg()....
[Short, Long] = movavg(Asset, Lead, Lag, Alpha)

the cyclist
the cyclist on 28 Jun 2013
This page of the MATLAB documentation has an example of using the filter() command to calculate a moving average:
  1 Comment
Dirk
Dirk on 28 Jun 2013
Thanks. The filter function is set to average data from the previous n measurements. Is there a simple way to specify a different averaging criteria? Thanks

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Jan
Jan on 28 Jun 2013
There are many moving average filters in the FileExchange. Whenever a standard problem occurs, looking in the FEX is a good idea:

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