A family of Bounded Component Analysis algorithms

Abstract

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.