Function File: a = aryule (x, p) ¶

Function File: [a, v, k] = aryule (x, p) ¶

Fit an AR (p)-model with Yule-Walker estimates.

x

data vector to estimate

a

AR coefficients

v

variance of white noise

k

reflection coefficients for use in lattice filter

The power spectrum of the resulting filter can be plotted with pyulear(x, p), or you can plot it directly with ar_psd(a,v,...).

See also: pyulear, power, freqz, impz – for observing characteristics of the model arburg – for alternative spectral estimators

Example: Use example from arburg, but substitute aryule for arburg.

Note: Orphanidis ’85 claims lattice filters are more tolerant of truncation errors, which is why you might want to use them. However, lacking a lattice filter processor, I haven’t tested that the lattice filter coefficients are reasonable.

Demonstration 1

 % use demo('pyulear')

Package: signal