Main Content

이 번역 페이지는 최신 내용을 담고 있지 않습니다. 최신 내용을 영문으로 보려면 여기를 클릭하십시오.

상관 모델

상관 분석을 사용하여 획득한 임펄스 응답 모델

System Identification측정된 데이터에서 동적 시스템의 모델 식별하기


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

예제 및 방법

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.