arcov (Signal Processing Toolbox)

Compute an estimate of AR model parameters using the covariance method.

Syntax

a = arcov(x,p)
[a,e] = arcov(x,p)

Description

a = arcov(x,p)

uses the 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 prediction error in the least-squares sense. Vector a contains the normalized estimate of the AR system parameters, A(z), in descending powers of z.

Because the method characterizes the input data using an all-pole model, the correct choice of the model order p is important.

[a,e] = arcov(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.
`armcov`	Compute an estimate of AR model parameters using the modified covariance method.
`aryule`	Compute an estimate of AR model parameters using the Yule-Walker method.
`lpc`	Linear prediction coefficients.
`pcov`	Power spectrum estimate using the covariance method.
`prony`	Prony's method for time domain IIR filter design.

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