MATLAB: Different kind of normalization

bsxfunnormalizestandard normal

I have read in Matlab that normalization of a vector is u/norm(u).
However, I have a matrix (N x N)where the columns are different vectors. I want for each element of column vectors to do something like: (u(i) – mean(u))/std(u) without looping so that at the end of it each column vectors are bunch of standard normals.
Is there a standard way to do it in matlab or do I really have to code the loop.

Best Answer

% Create standard normal distributed samples with std = 100;
A = randn(100000,10)*100;
% Normalize
B = bsxfun(@rdivide,bsxfun(@minus,A,mean(A)), std(A));
% Check first column
hist(B(:,1),100)
Note that mean and std operate along rows, i.e. for a matrix they give a result for each column.
Oleg
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