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.

Functions

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

Topics

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.