[scilab-Users] Re: reducing timeseries dataset for later on linear interpolation

[GOBILLOT Gilles 116128]

Hi David,

A simple way to under-sampling datas is :

Undersamplingfactor=4;
Dat_undersamp=dat(1: Undersamplingfactor:$);

But if datas are physical signals you will have an aliasing problem
 (http://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem#Aliasing in English,
 http://www-prima.imag.fr/Prima/jlc/Courses/2000/ENSI2.TS/ENSI2.TS.S5.pdf = in French)

So, in this case, you've to apply an anti-alisasing filter BEFORE the under-sampling.

Hope it will help you

Gilles

-----Message d'origine-----
De : CHEZE David 227480 
Envoyé : jeudi 31 mai 2012 09:25
À : users at lists.scilab.org
Objet : [scilab-Users] Re: reducing timeseries dataset for later on linear interpolation

Hi,

I've done it that way: 

dat=[0 0 1 3 2 2 0 0 0 0 2 4 2 4 4 2 0 0 0 0];
plot2d(dat)
datp=diff(dat);
datp_1=[datp(1) datp(1:$-1)];
k=find(datp<>datp_1)
datr=dat(k);
plot2d(k,datr)

i should have add the first point of dat in datr to have exactly the same curve but it works.
Is there a more direct and efficient way to do that in Scilab?

Thanks for your comment,

David



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