mne_denoise.dss.denoisers.BandpassBias#

class mne_denoise.dss.denoisers.BandpassBias(freq_band: tuple[float, float], sfreq: float, *, order: int = 4, method: str = 'butter')[source]#

Bandpass filter bias for narrow-band rhythm extraction.

Applies a bandpass filter to emphasize a specific frequency band, useful for extracting oscillatory sources (alpha, beta, etc.).

Parameters:

  • freq_band (tuple of float) – (low_freq, high_freq) defining the passband in Hz.

  • sfreq (float) – Sampling frequency in Hz.

  • order (int) – Filter order. Default 4.

  • method (str) – Filter design method: ‘butter’ or ‘fir’. Default ‘butter’.

Examples

>>> from mne_denoise.dss.denoisers import BandpassBias
>>> bias = BandpassBias(freq_band=(8, 12), sfreq=250)  # Alpha band
>>> dss.fit(data)

See also

mne_denoise.dss.denoisers.PeakFilterBias

For strictly periodic signals.

References

Särelä & Valpola (2005). Section 4.1.2 “DENOISING BASED ON FREQUENCY CONTENT”

__init__(freq_band: tuple[float, float], sfreq: float, *, order: int = 4, method: str = 'butter') → None[source]#

Methods

__init__(freq_band, sfreq, *[, order, method])

apply(data)

Apply bandpass filter bias.