Signal Processing Toolbox™

arburg - Estimate AR model parameters using Burg method

Syntax

a = arburg(x,p)
[a,e] = arburg(x,p)
[a,e,k] = arburg(x,p)

Description

a = arburg(x,p) uses the Burg method to fit a pth order autoregressive (AR) model to the input signal, x, by minimizing (least squares) the forward and backward prediction errors while constraining the AR parameters to satisfy the Levinson-Durbin recursion. x is assumed to be the output of an AR system driven by white noise. Vector a contains the normalized estimate of the AR system parameters, A(z), in descending powers of z.

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

[a,e] = arburg(x,p) returns the variance estimate, e, of the white noise input to the AR model.

[a,e,k] = arburg(x,p) returns a vector, k, of reflection coefficients.

See Also

arcov, armcov, aryule, lpc, pburg, prony

angle

arcov