moabb.pipelines.features.ExtendedSSVEPSignal#
- class moabb.pipelines.features.ExtendedSSVEPSignal[source]#
Prepare FilterBank SSVEP EEG signal for estimating extended covariances.
Riemannian approaches on SSVEP rely on extended covariances matrices, where the filtered signals are contenated to estimate a large covariance matrice.
FilterBank SSVEP EEG are of shape (n_trials, n_channels, n_times, n_freqs) and should be convert in (n_trials, n_channels*n_freqs, n_times) to estimate covariance matrices of (n_channels*n_freqs, n_channels*n_freqs).