Multi Dimensional ICA to Separate Correlated Sources

There are two linear transformations to be considered, one operating inside thechannels (0) and one operating between the different channels (W). The two transformations are estimated in two adjacent leA steps. There are mainly two advantages, that can be taken from the first transformation: (i) By arranging independence among the columns of the transformed patches, the average transinformation betweendifferent channels is decreased.