||Subtract offset or trend from data signals|
||Add offsets or trends to data signals|
||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|
||Resample time-domain data by decimation or interpolation (requires Signal Processing Toolbox software)|
||Data offset and trend information|
||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|
Subtract mean values from data, and specify estimation and validation data.
This example shows how to create a multi-experiment, time-domain data set by merging only the accurate data segments and ignoring the rest.
Before you can perform this task, you must have regularly-sampled, steady-state time-domain data imported into the System Identification app.
Before you can perform this task, you must have time-domain
data as an
Use the System Identification app to resample time-domain data.
The System Identification app lets you filter time-domain data using a fifth-order Butterworth filter by enhancing or selecting specific passbands.
Handling missing or erroneous data values.
Removing and restoring constant offsets and linear trends in data signals.
Decimating and interpolating (resampling) data.
Deciding whether to filter data before model estimation and how to prefilter data.
stores column-wise input data, and the
OutputData property stores column-wise output data.
The horizontal and vertical concatenation of
combine information in the
ResponseData properties of these objects.