|Subtract offset or trend from time-domain signals contained in
|Add offsets or trends to time-domain data signals stored in |
|Difference signals in iddata objects|
|Filter data using user-defined passbands, general filters, or Butterworth filters|
|Reconstruct missing input and output data|
|Shift data sequences|
|Resample time-domain data by decimation or interpolation|
|Option set for |
|(Not recommended) Resample time-domain data that is stored in an
|Create trend information object to store offset, mean, and trend information for
time-domain signals stored in |
|Change frequency units of frequency-response data model|
|Delete specified data from frequency response data (FRD) models|
|Offset and linear trend slope values for detrending data|
Examples and How To
- Preprocess Data Using Quick Start
Subtract mean values from data, and specify estimation and validation data.
- Extract and Model Specific Data Segments
This example shows how to create a multi-experiment, time-domain data set by merging only the accurate data segments and ignoring the rest.
- How to Detrend Data Using the App
Before you can perform this task, you must have regularly-sampled, steady-state time-domain data imported into the System Identification app.
- How to Detrend Data at the Command Line
Before you can perform this task, you must have time-domain data as an
- Resampling Data Using the App
Use the System Identification app to resample time-domain data.
- Resampling Data at the Command Line
resampleto decimate and interpolate time-domain
- How to Filter Data Using the App
The System Identification app lets you filter time-domain data using a fifth-order Butterworth filter by enhancing or selecting specific passbands.
- How to Filter Data at the Command Line
idfiltto apply passband and other custom filters to a time-domain or a frequency-domain
- Handling Missing Data and Outliers
Handling missing or erroneous data values.
- Handling Offsets and Trends in Data
Removing and restoring constant offsets and linear trends in data signals.
- Resampling Data
Decimating and interpolating (resampling) data.
- Filtering Data
Deciding whether to filter data before model estimation and how to prefilter data.