The preprocessing was done using an EEG lab toolbox (Delorme et al. 2011), where the signal was off-line referenced to linked mastoids (recorded with two more electrodes) and filtered in a range of 1 Hz to 45 Hz with zero phase-shift filters.
Feeds containing proteins and proteins with cells have been filtered using a range of membranes of largely different pore sizes.
The Landolt Cs were either low-pass or high-pass Gaussian filtered with a range of cutoff object spatial frequencies (cycles per letter) to limit their frequency content.
The alamut-HT output formed the basis of a variant report that could be filtered using a range of parameters with AgileExomeFilter (Fig. 1B; http://dna.leeds.ac.uk/agile).ac.uk/agile
Recorded slow wave data can be filtered via a range of inbuilt techniques, efficiently analyzed via automated event-detection and cycle clustering algorithms, and high quality isochronal activation maps, velocity field maps, amplitude maps, frequency (time interval) maps and data animations can be rapidly generated.
Since the primary question of interest is the influence of the tuning parameter t, this example considers a fixed window half-width parameter (specifically, K=5, yielding an 11-point moving window filter) and examines filter performance over a range of t values.
Therefore, data from KUJ were processed into time-series data of Pi 2 wave energy (Uozumi et al.2000), defined as an envelope of ΔH2 (ΔH: filtered H with a range of 40 to 150 s) to evaluate the background disturbance and to estimate the maximum energy value and time of each Pi 2. We defined the background disturbance as the average Pi 2 wave energy 5 to 10 min before the time of maximum energy.
The introduction of micromechanical actuators, utilizing electrothermal and electrostatic principles, allows wavelength tuning of the filter over a range of more than 40 nm in the 1.55 μm wavelength regime.
Before calculating the spectra, we applied a Butterworth band-pass filter with a range of 10 300 s to the original data to attenuate the background trend and high-frequency noise.
In our case, a mean filter with a range of three pixels was applied (i.e., the averaged value of a 3 × 3 pixel square was taken as the new value of the central pixel in this square).
