Truncating Data Sets of Different Size

OK, this should be fairly simple but I'm still not sure how to go about it. I have many sets of data, each with somewhere between 35000 and 40000 data points. I need to compare these data sets but I only need to compare them to the point of the lowest number of data points between the sets. So if I have sets 1, 2, and 3 with 36000, 37500, and 40000 data points respectively, and I compare sets 1 and 2 I am only using the first 36000 data points of the second set. Or if I compare sets 1, 2, and 3 I am only using the first 36000 data points of the second and third sets. What I need, I suppose, is a way to store my data in separate arrays and then delete the unneeded data in each array before the comparison. Thank you for your help.

[Azzi Abdelmalek]

This is not clear, give a short example with 3 vectors and give the expected result

Answer 1

[dpb]

Given x,y,z as the three data vectors,

lmin=min([length(x) length(y) length(z)]);

Now just use

[x|y|z](1:lmin)

for whatever you need to do. Or, to shorten the notation, simply write

x=[x(1:lmin) y(1:lmin) z(1:lmin)];
clear y z

and the various columns

res=yourcomparisonfunction( x(1,:),x(2,:) );

say, for x and y. Or however your computations go, of course.