braindecode.preprocessing.exponential_moving_standardize#
- braindecode.preprocessing.exponential_moving_standardize(data, factor_new=0.001, init_block_size=None, eps=0.0001)[source]#
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
- Returns
standardized – Standardized data.
- Return type
np.ndarray (n_channels, n_times)
Examples using braindecode.preprocessing.exponential_moving_standardize
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![Searching the best data augmentation on BCIC IV 2a Dataset](../_images/sphx_glr_plot_data_augmentation_search_thumb.png)
Searching the best data augmentation on BCIC IV 2a Dataset
Searching the best data augmentation on BCIC IV 2a Dataset
![Fingers flexion decoding on BCIC IV 4 ECoG Dataset](../_images/sphx_glr_plot_bcic_iv_4_ecog_trial_thumb.png)
Fingers flexion decoding on BCIC IV 4 ECoG Dataset
Fingers flexion decoding on BCIC IV 4 ECoG Dataset
![Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset](../_images/sphx_glr_plot_bcic_iv_4_ecog_cropped_thumb.png)
Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset
Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset