Moving Average Function using a sliding window
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Implement the moving average function, using a fixed window size of 10. Input variables: x – A vector containing a series of values that are to be smoothed. Output variables: y – A vector the same size as x, which contains the moving average. The elements of y satisfy:
y(i) = average of elements of x at positions from 1 to i, if 1 ≤ i ≤ 10; and
y(i) = average of elements of x at the 10 positions leading up to and including i, if i > 10.
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Image Analyst
on 31 Mar 2015
For what it's worth, I would have used conv() twice and divided them. Not sure how you did it. If you have the Curve Fitting Toolbox, you could use smooth()
Description
yy = smooth(y) smooths the data in the column vector y using a moving average filter. Results are returned in the column vector yy. The default span for the moving average is 5.
The first few elements of yy are given by
yy(1) = y(1)
yy(2) = (y(1) + y(2) + y(3))/3
yy(3) = (y(1) + y(2) + y(3) + y(4) + y(5))/5
yy(4) = (y(2) + y(3) + y(4) + y(5) + y(6))/5
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