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corr(G) Scilab Function corr(G)
NAME
corr - correlation, covariance
CALLING SEQUENCE
[cov,Mean]=corr(x,[y],nlags)
[cov,Mean]=corr('fft',xmacro,[ymacro],n,sect)
[w,xu]=corr('updt',x1,[y1],w0)
[w,xu]=corr('updt',x2,[y2],w,xu)
...
[wk]=corr('updt',xk,[yk],w,xu)
PARAMETERS
x : a real vector
y : a real vector, default value x.
nlags : integer, number of correlation coefficients desired.
xmacro : a scilab external (see below).
ymacro : a scilab external (see below), default value xmacro
n : an integer, total size of the sequence (see below).
sect : size of sections of the sequence (see below).
xi : a real vector
yi : a real vector,default value xi.
cov : real vector, the correlation coefficients
Mean : real number or vector, the mean of x and if given y
DESCRIPTION
Computes
n - m
====
\ 1
cov(m) = > (x(k) - xmean) (y(m+k) - ymean) * ---
/ n
====
k = 1
for m=0,..,nlag-1 and two vectors x=[x(1),..,x(n)]
y=[y(1),..,y(n)]
Note that if x and y sequences are differents corr(x,y,...) is different
with corr(y,x,...)
Short sequences:
[cov,Mean]=corr(x,[y],nlags) returns the first nlags correlation coeffi-
cients and Mean = mean(x) (mean of [x,y] if y is an argument). The
sequence x (resp. y) is assumed real, and x and y are of same dimension n.
Long sequences:
[cov,Mean]=corr('fft',xmacro,[ymacro],n,sect)
Here xmacro is either
- a function of type [xx]=xmacro(sect,istart) which returns a vector xx
of dimension nsect containing the part of the sequence with indices
from istart to istart+sect-1.
- a fortran subroutine which performs the same calculation. (See the
source code of dgetx for an example). n = total size of the sequence.
sect = size of sections of the sequence. sect must be a power of 2.
cov has dimension sect. Calculation is performed by FFT.
"Updating method":
[w,xu]=corr('updt',x1,[y1],w0)
[w,xu]=corr('updt',x2,[y2],w,xu)
...
wk=corr('updt',xk,[yk],w,xu)
With this calling sequence the calculation is updated at each call to corr.
w0 = 0*ones(1,2*nlags);
nlags = power of 2.
x1,x2,... are parts of x such that x=[x1,x2,...] and sizes of xi a power of
2. To get nlags coefficients a final fft must be performed c=fft(w,1)/n;
cov=c(1nlags) (n is the size of x (y)). Caution: this calling sequence
assumes that xmean = ymean = 0.
EXAMPLE
x=%pi/10:%pi/10:102.4*%pi;
rand('seed');rand('normal');
y=[.8*sin(x)+.8*sin(2*x)+rand(x);.8*sin(x)+.8*sin(1.99*x)+rand(x)];
c=[];
for j=1:2,for k=1:2,c=[c;corr(y(k,:),y(j,:),64)];end;end;
c=matrix(c,2,128);cov=[];
for j=1:64,cov=[cov;c(:,(j-1)*2+1:2*j)];end;
rand('unif')
//
rand('normal');x=rand(1,256);y=-x;
deff('[z]=xx(inc,is)','z=x(is:is+inc-1)');
deff('[z]=yy(inc,is)','z=y(is:is+inc-1)');
[c,mxy]=corr(x,y,32);
x=x-mxy(1)*ones(x);y=y-mxy(2)*ones(y); //centring
c1=corr(x,y,32);c2=corr(x,32);
norm(c1+c2,1)
[c3,m3]=corr('fft',xx,yy,256,32);
norm(c1-c3,1)
[c4,m4]=corr('fft',xx,256,32);
norm(m3,1),norm(m4,1)
norm(c3-c1,1),norm(c4-c2,1)
x1=x(1:128);x2=x(129:256);
y1=y(1:128);y2=y(129:256);
w0=0*ones(1:64); //32 coeffs
[w1,xu]=corr('u',x1,y1,w0);w2=corr('u',x2,y2,w1,xu);
zz=real(fft(w2,1))/256;c5=zz(1:32);
norm(c5-c1,1)
[w1,xu]=corr('u',x1,w0);w2=corr('u',x2,w1,xu);
zz=real(fft(w2,1))/256;c6=zz(1:32);
norm(c6-c2,1)
rand('unif')
// test for Fortran or C external
//
deff('[y]=xmacro(sec,ist)','y=sin(ist:(ist+sec-1))');
x=xmacro(100,1);
[cc1,mm1]=corr(x,2^3);
[cc,mm]=corr('fft',xmacro,100,2^3);
[cc2,mm2]=corr('fft','corexx',100,2^3);
[maxi(abs(cc-cc1)),maxi(abs(mm-mm1)),maxi(abs(cc-cc2)),maxi(abs(mm-mm2))]
deff('[y]=ymacro(sec,ist)','y=cos(ist:(ist+sec-1))');
y=ymacro(100,1);
[cc1,mm1]=corr(x,y,2^3);
[cc,mm]=corr('fft',xmacro,ymacro,100,2^3);
[cc2,mm2]=corr('fft','corexx','corexy',100,2^3);
[maxi(abs(cc-cc1)),maxi(abs(mm-mm1)),maxi(abs(cc-cc2)),maxi(abs(mm-mm2))]
SEE ALSO
fft
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