| Signal Processing Toolbox | Search Help Desk |
| armcov | See Also |
Compute an estimate of AR model parameters using the modified covariance method.
Syntax
a = armcov(x,p) [a,e] = armcov(x,p)
Description
a = armcov(x,p)
uses the modified covariance method to fit a p-th order autoregressive (AR) model to the input signal, x, which is assumed to be the output of an AR system driven by white noise. This method minimizes the forward and backward prediction errors in the least-squares sense. Vector a contains the normalized estimate of the AR system parameters, A(z), in descending powers of z.
p is important.
[a,e] = armcov(x,p)
returns the variance estimate, e, of the white noise input to the AR model.
See Also
arburg |
Compute an estimate of AR model parameters using the Burg method. |
arcov |
Compute an estimate of AR model parameters using the covariance method. |
aryule |
Compute an estimate of AR model parameters using the Yule-Walker method. |
lpc |
Linear prediction coefficients. |
pmcov |
Power spectrum estimate using the modified covariance method. |
prony |
Prony's method for time domain IIR filter design. |