This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English verison of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.


Covariance spectrum


Hs = spectrum.cov
Hs = spectrum.cov(order)



The use of spectrum.cov is not recommended. Use pcov instead.

Hs = spectrum.cov returns a default covariance spectrum object, Hs, that defines the parameters for the covariance spectral estimation algorithm. The covariance algorithm estimates the spectral content by fitting an autoregressive (AR) linear prediction model of a given order to the signal.

Hs = spectrum.cov(order) returns a spectrum object, Hs with the specified order. The default value for order is 4.


See pcov for more information on the covariance algorithm.


Define a fourth order autoregressive model and view its power spectral density using the covariance algorithm.

x=filter(1,[1 1/2 1/3 1/4 1/5],x);   % 4th order AR filter
Hs=spectrum.cov;                     % 4th order AR model

See Also

| | |

Introduced before R2006a

Was this topic helpful?