Fast technique for normalizing a matrix in MATLAB

Question

I want to normalise each column of a matrix in Matlab. I have tried two implementations:

Option A:

mx=max(x);
mn=min(x);
mmd=mx-mn;
for i=1:size(x,1)
    xn(i,:)=((x(i,:)-mn+(mmd==0))./(mmd+(mmd==0)*2))*2-1; 
end

Option B:

mn=mean(x);
sdx=std(x);
for i=1:size(x,1)
    xn(i,:)=(x(i,:)-mn)./(sdx+(sdx==0));
end

However, these options take too much time for my data, e.g. 3-4 seconds on a 5000x53 matrix. Thus, is there any better solution?

Answer 1

Remember, in MATLAB, vectorizing = speed.

If A is an M x N matrix,

A = rand(m,n);
minA = repmat(min(A), [size(A, 1), 1]);
normA = max(A) - min(A);               % this is a vector
normA = repmat(normA, [length(normA) 1]);  % this makes it a matrix
                                       % of the same size as A
normalizedA = (A - minA)./normA;  % your normalized matrix