Correlation Models

Impulse-response models obtained using correlation analysis

Time-domain correlation analysis refers to nonparametric estimation of the impulse response of dynamic systems as a finite impulse response (FIR) model from the data. The estimated model is stored as a transfer function object.

Apps

System Identification

Identify models of dynamic systems from measured data

Functions

`cra`	Estimate impulse response using input/output data prewhitening before correlation analysis
`impulseest`	Nonparametric impulse response estimation
`impulseestOptions`	Options set for `impulseest`
`era`	Estimate state-space model from impulse response data using Eigensystem Realization Algorithm (ERA) (Since R2022b)
`getpvec`	Obtain model parameters and associated uncertainty data
`setpvec`	Modify values of model parameters

Topics

What Is Time-Domain Correlation Analysis?
Time-domain correlation analysis refers to nonparametric estimation of the impulse response of dynamic systems as a finite impulse response (FIR) model from the data.
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.