User`s guide

Modified Covariance AR Estimator

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5Modified Covariance AR Estimator

Purpose Compute an estimate of AR model parameters using the modified covariance

method.

Library Estimation / Parametric Estimation

Description The Modified Covariance AR Estimator block uses the modified covariance

method to fit an autoregressive (AR) model to the input data. This method

minimizes the forward and backward prediction errors in the least-squares

sense. 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 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

Estimation order

The order of the AR model, p.

References Kay, S. M. Modern Spectral Estimation: Theory and Application. Englewood

Cliffs, NJ: Prentice-Hall, 1988.

Hz()

Az()

------------

1 a 2()z

1–

… ap 1+()z

p–

+++

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