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A Minimum-Range Approach to Blind Extraction of Bounded Sources
2007
IEEE Transactions on Neural Networks
In spite of the numerous approaches that have been derived for solving the independent component analysis (ICA) problem, it is still interesting to develop new methods when, among other reasons, specific a priori knowledge may help to further improve the separation performances. In this paper, the minimum-range approach to blind extraction of bounded source is investigated. The relationship with other existing well-known criteria is established. It is proved that the minimum-range approach is a
doi:10.1109/tnn.2006.889941
pmid:17526346
fatcat:bul4isncr5fgxizojqzgtl4eze