Documentation

This is machine translation

Translated by Microsoft
Mouse over text to see original. Click the button below to return to the English verison of the page.

Correlation Models

Impulse-response models obtained using correlation analysis

Apps

System Identification Identify models of dynamic systems from measured data

Functions

cra Estimate impulse response using prewhitened-based correlation analysis
impulseest Nonparameteric impulse response estimation
getpvec Model parameters and associated uncertainty data
setpvec Modify value of model parameters
impulseestOptions Options 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.

Concepts

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.

Was this topic helpful?