(To be removed) Estimate of autoregressive (AR) model parameters using Burg method
The dsp.BurgAREstimator
System
object™ will be removed in a future release. Use arburg
instead. For more information, see Compatibility Considerations.
The BurgAREstimator
object computes the estimate of
the autoregressive (AR) model parameters using the Burg method.
To compute the estimate of the AR model parameters:
Define and set up your System object. See Construction.
Call step
to compute the estimate according
to the properties of dsp.BurgAREstimator
. The
behavior of step
is specific to each object in
the toolbox.
Starting in R2016b, instead of using the step
method to perform the operation defined by the System
object, you can call the object with arguments, as if it were a function. For
example, y = step(obj,x)
and y = obj(x)
perform equivalent operations.
burgarest = dsp.BurgAREstimator
returns a Burg BurgAREstimator
System
object, burgarest
, that performs parametric
AR
estimation using the Burg maximum entropy
method.
burgarest = dsp.BurgAREstimator('
returns a Burg PropertyName
',PropertyValue
,...)AR
estimator object, burgarest
, with each specified property set to the
specified value.
|
Enable output of polynomial coefficients Set this property to |
|
Enable output of reflection coefficients Set this property to |
|
Source of estimation order Specify how to determine estimator order as |
|
Order of AR model Set the AR model estimation order to a real positive integer. This
property applies when you set the |
step | Normalized estimate of AR model parameter |
Common to All System Objects | |
---|---|
release | Allow System object property value changes |
Note: This example runs only in
R2016b or later. If you are using an earlier release, replace each call to the
function with the equivalent step
syntax. For example,
myObject(x) becomes step(myObject,x).
Use the dsp.BurgAREstimator
System object to estimate the
parameters of an AR model.
rng default; % Use default random number generator and seed noise = randn(100,1); % Normalized white Gaussian noise x = filter(1,[1 1/2 1/3 1/4 1/5],noise); burgarest = dsp.BurgAREstimator(... 'EstimationOrderSource', 'Property', ... 'EstimationOrder', 4); [a, g] = burgarest(x); x_est = filter(g, a, x); plot(1:100,[x x_est]); title('Original and estimated signals'); legend('Original', 'Estimated');
This object implements the algorithm, inputs, and outputs described on the Burg AR Estimator block reference page. The object properties correspond to the block parameters, except:
Output(s) block parameter corresponds to the AOutputPort and the KOutputPort object properties. |