Documentation |
ts1 = idealfilter(ts, interval, filtertype)
ts1 = idealfilter(ts, interval, filtertype, index)
ts1 = idealfilter(ts, interval, filtertype) applies an ideal filter of filtertype to one or more frequency intervals that interval specifies for the timeseries object, ts.
ts1 = idealfilter(ts, interval, filtertype, index) applies an ideal filter and uses the optional index integer array to specify the columns or rows to filter.
Ideal filters require data to have a mean of zero and prepare the data by subtracting its mean. You can restore the filtered signal amplitude by adding the mean of the input data to the filter output values.
Use the ideal notch filter when you want to remove variations in a specific frequency range. Alternatively, use the ideal pass filter to allow only the variations in a specific frequency range.
If the time-series data is sampled nonuniformly, filtering resamples this data on a uniform time vector.
All NaNs in the time series are interpolated before filtering, using the interpolation method you assigned to the timeseries object.
ts1 |
The timeseries object that results when you apply an ideal filter to the original timeseries object. |
Filters are ideal in the sense that they are not realizable. An ideal filter is noncausal and the ends of the filter amplitude are perfectly flat in the frequency domain.