Matlab Code Optimization in calulating euclidean distance between vectors

The following code is taking a lot of time for execution say if N=135. How can I make it faster. Is there an alternative to calculate the euclidean distance between the vectors.

FVCompare= zeros(N,N); file = 'FV';

for i=1:N

    sname = strcat(file,int2str(i));
    sfile = strcat('FeatureVectors\',sname);
    srcfile = strcat(sfile,'.mat');

    for count=1:N
        dname = strcat(file,int2str(count));
        dfile = strcat('FeatureVectors\',dname);
        destfile = strcat(dfile,'.mat');

        Vec1 = load (srcfile); %loads FeatureVector-1
        Vec2 = load (destfile); %loads FeatureVectors to be compared

        var1 = struct2cell(Vec1);
        fv1=var1{:};
        var2 = struct2cell(Vec2);
        fv2=var2{:};

        %Finding Euclidean Distance
        R = norm(fv1-fv2);

        FVCompare(i,count) = R;
    end
end

Answer 1

[Alan Weiss]

If you use profile to check which part of your code is taking the most time, I guess you will find that the load operations are your bottleneck. If this guess turns out to be true, then you need to find a way to load just one data file. For example, you could concatenate all your data files into one big matrix, with possibly different lengths that you store in another file. Then just load once, and process the data in chunks.

Alan Weiss

MATLAB mathematical toolbox documentation

[.. Vamshi]

I can load them at once in the beginning so no problem there. The problem is I am calculating euclidean distance of each vector with one another which executes 135x135 (if N=135). I want to cut the time in computation here. So help me in this regard.