User`s guide

Yule-Walker Method
5-549
5Yule-Walker Method
Purpose Compute a parametric estimate of the spectrum using the Yule-Walker AR
method.
Library Estimation / Power Spectrum Estimation
Description The Yule-Walker Method block estimates the power spectral density (PSD) of
the input using the Yule-Walker AR method. This method, also called the
autocorrelation method, fits 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 Levinson-Durbin recursion.
The input is a sample-based vector (row, column, or 1-D) or frame-based vector
(column only) representing a frame of consecutive time samples from a
single-channel signal. The block’s output (a column vector) is the estimate of
the signal’s power spectral density at N
fft
equally spaced frequency points in
the range [0,F
s
), where F
s
is the signal’s sample frequency.
When
Inherit estimation order from input dimensions is selected, the order
of the all-pole model is one less that the input frame size. Otherwise, the order
is the value specified by the
Estimation order parameter. The spectrum is
computed from the FFT of the estimated AR model parameters.
When
Inherit FFT length from estimation order is selected, N
fft
is specified
by (estimation order + 1), which must be a power of 2. When
Inherit FFT
length from estimation order
is not selected, N
fft
is specified as a power of 2
by the
FFT length parameter, and the block zero pads or truncates the input
to N
fft
before computing the FFT. The output is always sample-based.
See the Burg Method block reference for a comparison of the Burg Method,
Covariance Method, Modified Covariance Method, and Yule-Walker AR
Estimator blocks. The Yule-Walker AR Estimator and Burg Method blocks
return similar results for large buffer lengths.