braindecode.preprocessing.exponential_moving_demean¶
- braindecode.preprocessing.exponential_moving_demean(data, factor_new=0.001, init_block_size=None)¶
Perform exponential moving demeanining.
Compute the exponental moving mean \(m_t\) at time t as \(m_t=\mathrm{factornew} \cdot mean(x_t) + (1 - \mathrm{factornew}) \cdot m_{t-1}\).
Deman the data point \(x_t\) at time t as: \(x'_t=(x_t - m_t)\).
- Parameters
- data: np.ndarray (n_channels, n_times)
- factor_new: float
- init_block_size: int
Demean data before to this index with regular demeaning.
- Returns
- demeaned: np.ndarray (n_channels, n_times)
Demeaned data.