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Blind source separation (BSS) methods have received extensive attention over the past two decades; thanks to its wide applicability in a number of areas such as biomedical engineering, audio signal processing, and telecommunications. The problem of source separation is an inductive inference problem, as only limited information, eg, the sensor observations, is available to infer the most probable source estimates. The aim of BSS is to process these observations (acquired by sensors or sensor arrays) in such a way that the original unknown source signals are extracted by, eg, an adaptive system, or separated simultaneously using, eg, a block (or batch)-based algorithm, without knowing or with very limited information about the characteristics of the transmission channels through which the sources propagate to the sensors. Independent component analysis (ICA) is one of the early and most widely used …