Scilab Reference Manual |
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pspect — cross-spectral estimate between 2 series
[sm,cwp]=pspect(sec_step,sec_leng,wtype,x,y,wpar)
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 |
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.
Digital Signal Processing by Oppenheim and Schafer
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');
C. B.
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