Scilab Function cspect - spectral estimation (correlation method)
Calling Sequence
- [sm,cwp]=cspect(nlags,ntp,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
- nlags
: number of correlation lags (positive integer)
- ntp
: number of transform points (positive integer)
- wtype
: string : 're','tr','hm','hn','kr','ch' (window type)
- wpar
: optional window parameters for wtype='kr', wpar>0 and for wtype='ch', 0 < wpar(1) < .5, wpar(2) > 0
- sm
: power spectral estimate in the interval [0,1]
- cwp
: calculated value of unspecified Chebyshev window parameter
Description
Spectral estimation using the correlation method.
Cross-spectral estimate of x and y is calculated when both
x and y are given. Auto-spectral estimate of x is calculated
if y is not given.
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));
sm=cspect(100,200,'tr',y);
smsize=maxi(size(sm));fr=(1:smsize)/smsize;
plot(fr,log(sm))
See Also
Author
C. Bunks ; Digital Signal Processing by Oppenheim and Schafer