Matlab Code Optimization in calulating euclidean distance between vectors
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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
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Respuestas (1)
Alan Weiss
el 12 de Feb. de 2013
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
1 comentario
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