braindecode.preprocessing.exponential_moving_demean#

braindecode.preprocessing.exponential_moving_demean(data, factor_new=0.001, init_block_size=None)[source]#

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: $x_t^{\prime }=(x_t-m_t)$.

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 – Demeaned data.

Return type:

np.ndarray (n_channels, n_times)