System object: dsp.BurgAREstimator
Normalized estimate of AR model parameter
[A,G] = step(H,X)
[K,G] = step(H,X)
[A,K,G] = step(H,X)
[A,G] = step(H,X) computes the normalized estimate of the AR model parameters to fit the input, X, in the least square sense. The input X must be a column vector. Output A is a column vector that contains the normalized estimate of the AR model polynomial coefficients in descending powers of z. The scalar G is the AR model gain.
[K,G] = step(H,X) returns K, a column vector containing the AR model reflection coefficients when you set the KOutputPort property to true and the AOutputPort property to false.
[A,K,G] = step(H,X) returns the AR model polynomial coefficients A, reflection coefficients K, and the scalar gain G when the AOutputPort and KOutputPort properties are both true.
Note: H specifies the System object™ on which to run this step method.
The object performs an initialization the first time the step method is executed. This initialization locks nontunable properties and input specifications, such as dimensions, complexity, and data type of the input data. If you change a nontunable property or an input specification, the System object issues an error. To change nontunable properties or inputs, you must first call the release method to unlock the object.