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

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