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Luca
Posts:
77
Registered:
6/6/12


Best way to "classify" a vector? ("averaging" subsampling)
Posted:
Mar 4, 2013 4:19 PM


Hi everyone. Let's suppose to have these two vectors:
t=0:0.01:1000; %timestamps val = rand(size(t)); %value associated with each timestamp
Now let's suppose I want to calculate the mean value of val in each interval of "t" broad "1". What would be the best way to do it? The dumbest would be something _like_ (I'm sure somebody will find a couple of minor errors :). But try to get the point!):
t2 = ceil (t); [t2,I]= unique (t2,'first'); [t2,J]=unique (t2,'last'); meanVal= zeros(max(t2(:),1); for i=1:numel(meanVal) meanVal(i) = mean(val(I(i):val(J(i)); end
Now... I know that matlab always has some built in functions that does all of these basic operations better and faster. So.... what would be a smarter way to do this??



