How to calculate the moving average of a finite duration data using sliding concept?

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Souarv De
Souarv De 2022-3-23
评论： Souarv De 2022-3-24
Ran in:
I want to compute the moving average of the data array as X = [2 3 4 5 6 8] using sliding window concept with window size of 4. This example is given in the following link. https://in.mathworks.com/help/dsp/ug/sliding-window-method-and-exponential-weighting-method.html .
For that, I am using the command movAvg = dsp.MovingAverage from DSP System Toolbox. But using that I am getting answer like as shown below.
X = [2 3 4 5 6 8];
movavgWindow = dsp.MovingAverage(4);
Y = movavgWindow(X)
Y = 1×6
0.5000 0.7500 1.0000 1.2500 1.5000 2.0000
But as per the link given above the actual answer would be like as shown below.
Y = [0.5 1.25 2.25 3.50 4.50 5.75];
So where is the mistake? Can anyone tell me why the answer is comming as so different even if I am using the same command as recommended in the documemt.

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Matt J
Matt J 2022-3-23
Ran in:
Both are wrong.
X = [2 3 4 5 6 8];
win=ones(1,4)/4;
Y = conv(X,win,'full')
Y = 1×9
0.5000 1.2500 2.2500 3.5000 4.5000 5.7500 4.7500 3.5000 2.0000
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Matt J
Matt J 2022-3-23
编辑：Matt J 2022-3-23
Ran in:
It is really so shocking that how the MATLAB inbult command can give wrong answers or there may be some mistake we are doing to understand about how the functions works.
Probably the latter, but I can't tell from the documentation what it's doing.
Then how to do this except selecting the range of Y from 1 to 6. Is there any way to do that?
One way:
X = [2 3 4 5 6 8];
Y=movmean(X,[3,0],'Endpoints',0)
Y = 1×6
0.5000 1.2500 2.2500 3.5000 4.5000 5.7500

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