Main Content





System IdentificationIdentify models of dynamic systems from measured data


craEstimate impulse response using prewhitened-based correlation analysis
impulseestNonparametric impulse response estimation
getpvecObtain model parameters and associated uncertainty data
setpvecModify values of model parameters
impulseestOptionsOptions set for impulseest


Estimate Impulse-Response Models Using System Identification App

Estimate in the app using time-domain correlation analysis.

Estimate Impulse-Response Models at the Command Line

Use impulseest command to estimate using correlation analysis.

Compute Response Values

Obtain numerical impulse- and step-response vectors as a function of time.

Identify Delay Using Transient-Response Plots

You can use transient-response plots to estimate the input delay, or dead time, of linear systems. Input delay represents the time it takes for the output to respond to the input.


What Is Time-Domain Correlation Analysis?

Time-domain correlation analysis refers to non-parametric estimation of the impulse response of dynamic systems as a finite impulse response (FIR) model from the data. The estimated model is stored as transfer function model object (idtf). For information about transfer function models, see What are Transfer Function Models?.

Data Supported by Correlation Analysis

Characteristics of data supported for estimation of impulse-response models.

Correlation Analysis Algorithm

Correlation analysis refers to methods that estimate the impulse response of a linear model, without specific assumptions about model orders.