A family of Bounded Component Analysis algorithms
Alper Tunga Erdogan · 2012
Bounded Component Analysis (BCA) has recently been introduced as an alternative method for the Blind Source Separation problem. Under the generic assumption on source boundedness, BCA provides a flexible framework for the separation of dependent (even correlated) as well as independent sources. This article provides a family of algorithms derived based on the geometric picture implied by the founding assumptions of the BCA approach. We also provide a numerical example demonstrating the ability of the proposed algorithms to separate mixtures of some dependent sources.