Algorithm 3 ICA based denoising of EEG signals

Input: X: EEG data matrix

Input: $n\_components$: number of independent components to estimate

Output: S: matrix of independent components

Output: A: estimated demixing matrix

Center and whiten the X.

Initialize A randomly.

repeat

Update A by exploiting non-Gaussianity of independent sources.

until convergence

Compute S from A and X.

Identify artifact components in S.

Remove artifact components from S.

Reconstruct cleaned data from S.

return S, A