```Date: Mar 4, 2013 4:30 PM
Author: Curious
Subject: Re: Best way to "classify" a vector? ("averaging" subsampling)

"Luca " <l.presottoRE@MOVE.campus.unimib.NOTit> wrote in message <kh334d\$k8h\$1@newscl01ah.mathworks.com>...> 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??% This sounds like you are trying to compute a "running average" of the vector.% If so, see the Examples section of doc filter
```