braindecode.preprocessing.exponential_moving_standardize¶
- braindecode.preprocessing.exponential_moving_standardize(data, factor_new=0.001, init_block_size=None, eps=0.0001)¶
Perform exponential moving standardization.
Compute the exponental moving mean \(m_t\) at time t as \(m_t=\mathrm{factornew} \cdot mean(x_t) + (1 - \mathrm{factornew}) \cdot m_{t-1}\).
Then, compute exponential moving variance \(v_t\) at time t as \(v_t=\mathrm{factornew} \cdot (m_t - x_t)^2 + (1 - \mathrm{factornew}) \cdot v_{t-1}\).
Finally, standardize the data point \(x_t\) at time t as: \(x'_t=(x_t - m_t) / max(\sqrt{->v_t}, eps)\).
- Parameters
- data: np.ndarray (n_channels, n_times)
- factor_new: float
- init_block_size: int
Standardize data before to this index with regular standardization.
- eps: float
Stabilizer for division by zero variance.
- Returns
- standardized: np.ndarray (n_channels, n_times)
Standardized data.
