Fig. 2. Hierarchy of linear BSS models.
Historically, BSS models have been made more general by: A) increasing the number of datasets which can be jointly analyzed [see Layout and Subsets]; B) moving from isolated sources to groups of sources in the same dataset [see Subsets]; C) exploiting SOS, HOS, or both [see Type of Statistics]. The arrows indicate the directions of increasing difficulty, model complexity, and generality. Highly general models can address MDM problems by incorporating lenient modeling choices.