Scilab Function

cspect - spectral estimation (correlation method)

### Sequence d'appel

  `[sm,cwp]=cspect(nlags,ntp,wtype,x,y,wpar)`

### Parametres

- `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.

### Exemples

    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))

### Voir aussi

`pspect`

### Auteur

C. Bunks ; Digital Signal Processing by Oppenheim and Schafer