Man Scilab

pspect Scilab Function

pspect - cross-spectral estimate between 2 series

Calling Sequence

[sm,cwp]=pspect(sec_step,sec_leng,wtype,x,y,wpar)

Parameters

x : data if vector, amount of input data if scalar
y : data if vector, amount of input data if scalar
sec_step : offset of each data window
sec_leng : length of each data window
wtype : window type (re,tr,hm,hn,kr,ch)
wpar : optional parameters for wtype='kr', wpar>0 for wtype='ch', 0<wpar(1)<.5, wpar(2)>0
sm : power spectral estimate in the interval [0,1]
cwp : unspecified Chebyshev window parameter

Description

Cross-spectral estimate between x and y if both are given and auto-spectral estimate of x otherwise. Spectral estimate obtained using the modified periodogram method.

Reference

Digital Signal Processing by Oppenheim and Schafer

Examples


rand('normal');rand('seed',0);
x=rand(1:1024-33+1);
//make low-pass filter with eqfir
nf=33;bedge=[0 .1;.125 .5];des=[1 0];wate=[1 1];
h=eqfir(nf,bedge,des,wate);
//filter white data to obtain colored data 
h1=[h 0*ones(1:maxi(size(x))-1)];
x1=[x 0*ones(1:maxi(size(h))-1)];
hf=fft(h1,-1);   xf=fft(x1,-1);yf=hf.*xf;y=real(fft(yf,1));
//plot magnitude of filter
//h2=[h 0*ones(1:968)];hf2=fft(h2,-1);hf2=real(hf2.*conj(hf2));
//hsize=maxi(size(hf2));fr=(1:hsize)/hsize;plot(fr,log(hf2));
//pspect example
sm=pspect(100,200,'tr',y);smsize=maxi(size(sm));fr=(1:smsize)/smsize;
plot(fr,log(sm));
rand('unif');

Author

C. B.

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