ts1 = idealfilter(ts, interval, filtertype)
ts1 = idealfilter(ts, interval, filtertype, index)
ts1 = idealfilter(
applies an ideal filter of ts
, interval
, filtertype
)filtertype
to one
or more frequency intervals that interval
specifies
for the timeseries
object, ts
.
ts1 = idealfilter(
applies an ideal filter and uses the optional ts
, interval
, filtertype
, index
)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 timeseries data is sampled nonuniformly, filtering resamples this data on a uniform time vector.
All NaN
s in the time series are
interpolated before filtering, using the interpolation method you
assigned to the timeseries
object.

The 

The frequency interval (specified in cycles per time unit) at
which you want the ideal filter applied. To specify several frequency
intervals, use an nby2 array of start and end frequencies, where 

A string specifying the type of filter you want to apply, either 

An integer array that specifies the columns or rows to filter
when 

The 
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.