This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English version of the page.

Note: This page has been translated by MathWorks. Click here to see
To view all translated materials including this page, select Country from the country navigator on the bottom of this page.

Parametric Modeling

Burg and Yule-Walker autoregressive models, Prony’s method

Estimate AR parameters of a signal. Estimate transfer functions starting from frequency-response data.


arburgAutoregressive all-pole model parameters — Burg’s method
arcovAutoregressive all-pole model parameters — covariance method
armcovAutoregressive all-pole model parameters — modified covariance method
aryuleAutoregressive all-pole model parameters — Yule-Walker method
invfreqsIdentify continuous-time filter parameters from frequency response data
invfreqzIdentify discrete-time filter parameters from frequency response data
prony Prony method for filter design
stmcbCompute linear model using Steiglitz-McBride iteration


Linear Prediction and Autoregressive Modeling

Compare two methods for determining the parameters of a linear filter: autoregressive modeling and linear prediction.

AR Order Selection with Partial Autocorrelation Sequence

Assess the order of an autoregressive model using the partial autocorrelation sequence.

Parametric Modeling

Study techniques that find the parameters for a mathematical model describing a signal, system, or process.