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

Use bsxfun instead of the loop. This may be a bit faster; however, it may also use more memory (which may be an issue in your case; if you're paging, everything'll be really slow).

To normalize with mean and std, you'd write

mn = mean(x);
sd = std(x);
sd(sd==0) = 1;

xn = bsxfun(@minus,x,mn);
xn = bsxfun(@rdivide,xn,sd);