braindecode.preprocessing.exponential_moving_demean

braindecode.preprocessing.exponential_moving_demean(data, factor_new=0.001, init_block_size=None)

Perform exponential moving demeaning.

Compute the exponential moving mean \(m_t\) at time t as a weighted average: \(m_t = \frac{\sum_{i=0}^t (1-\alpha)^i x_{t-i}}{\sum_{i=0}^t (1-\alpha)^i}\) where \(\alpha\) is factor_new.

Demean the data point \(x_t\) at time t as: \(x'_t=(x_t - m_t)\).

Parameters:

• data (ndarray[tuple[Any, ...], dtype[TypeVar(_ScalarT, bound= generic)]])

• factor_new (float)

• init_block_size (int | None) – Demean data before to this index with regular demeaning.

Returns:

demeaned – Demeaned data.

Return type:

np.ndarray (n_channels, n_times)