Optimizing a Sliding Window for Matrix Re-Assignment

I have a matrix, A, which is a massive NxM matrix where N is several millions and M is relatively small. and I would like to do an operation (xcorr() or std(), for example) on a window of this matrix, A(i:i+x,:), for i=1:N. However, using "for" loops ends up taking a lot of time since Matlab and "for" loops get along like me and my "ex" wife.

I'm trying to optimize it by creating a new matrix, B composed of the windows of A. For example, if

A=[1 2 3 4 5 6 8 9 10],

and the window size is x=3,

B= [1 2 3
    2 3 4
    3 4 5
    ...
    8 9 10]

Is there any way to optimize this using only vector/matrix operations in order to speed up processing?

[Eng. Fredius Magige]

You have post 3 times the same QUESTION, please do just once; any amendment might use comment to verify etc.

Put clear you task; note that and mostly vectorization handle it/assignment quickly (in fraction of minutes) Thanks

Answer 1

[Thorsten]

If you have the image processing toolbox, you can use:

 stdA3 = colfilt(A, [3 1], 'sliding', @std);

[Al Capwn]

Wowza, it's about 10x faster, thanks!