Yule-Walker AR Estimator (DSP Blockset)

Compute an estimate of AR model parameters using the Yule-Walker method.

Library

Parametric Estimation, in Estimation

Description

The Yule-Walker AR Estimator block uses the Yule-Walker AR method, also called the autocorrelation method, to fit an autoregressive (AR) model to the windowed input data by minimizing the forward prediction error in the least-squares sense. This formulation leads to the Yule-Walker equations, which are solved by the Levinson-Durbin recursion. The input is a frame of consecutive time samples, which is assumed to be the output of an AR system driven by white noise. The block computes the normalized estimate of the AR system parameters, A(z), independently for each successive input.

The order, p, of the all-pole model is specified by the Order parameter. The Yule-Walker AR Estimator and Burg AR Estimator blocks return similar results for large frame sizes.

The top output, A, contains the normalized estimate of the AR model coefficients in descending powers of z,

[1 a(2) ... a(p+1)]

The scalar gain, G, is provided at the bottom output (G).

Dialog Box

Prediction order: The order of the AR model. A value of -1 specifies a model order one less than the input frame size.

References

Kay, S. M. Modern Spectral Estimation: Theory and Application. Englewood Cliffs, NJ: Prentice-Hall, 1988.

Marple, S. L., Jr., Digital Spectral Analysis with Applications. Englewood Cliffs, NJ: Prentice-Hall, 1987.