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Correlation Models

Impulse-response models obtained using correlation analysis


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

Examples and How To

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.


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.

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.