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相関モデル
アプリ
System Identification | Identify models of dynamic systems from measured data |
関数
cra | Estimate impulse response using prewhitened-based correlation analysis |
impulseest | Nonparametric impulse response estimation |
getpvec | Obtain model parameters and associated uncertainty data |
setpvec | Modify values of model parameters |
impulseestOptions | Options set for impulseest |
例および操作のヒント
- 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.
概念
- 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.