User`s guide

Identifying Impulse-Response Models
Theresponsetoaninputu(t) is equal to the convolution of the impulse
response, as follows:
yt h t z uzdz
t
() ( )=−
()
⋅
∫
0
Data Supported by Correlation Analysis
You can estimate correlation analysis models from data with the follow i ng
characteristics:
• Real or complex time-domain
iddata object. To learn about estimating
time-series models , see Chapter 6, “Time Series M odel Identification”.
• Frequency-domain
iddata or idfrd object with the s ampling interval T≠0.
• Single- or m ultiple-output data.
How to E stimate Correlation Models Using the GUI
The following procedure assumes that you already imported your data into
the GUI and performed any necessary preprocessing operations. For more
information, see Chapter 1, “Data Processing”.
To estimate im pulse- and step-response models in the System Identification
Tool GUI using time-domain correlation analysis:
1 In the System Identification Tool GUI, se lect Estimate > Correlation
models to open the Correlation Model dialog box.
2 In the Time span (s) field, specify a scalar value as the time interval over
which the impulse or step response is calculated. For a scalar time span T,
the resulting response is plotted from -T/4 to T.
Tip You can also enter a 2-D vector in the format [min_value max_value].
3 In the Order of whitening filter field, specify the filter order.
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