Independent Subspace Analysis For Blind Signal Separation: Models And Algorithms

Abstract

As an extended independent component analysis (ICA) method for blind signal separation (BSS), independent subspace analysis (ISA) has more applications than ICA method. In this paper, we briefly present a new perspective of ISA for BSS. The general and detailed definition of the ISA model is given, the relationships between ICA and ISA methods is also discussed. Moreover, due to the fundamental difficulty in the ISA problem that it (specify it here) is not unique without extra constraints, we also review and discuss the separateness and uniqueness of the ISA model. At last, the state-of-art ISA algorithms are overviewed from different theoretical foundations. Some ISA algorithms based on the original relative gradient (natural gradient) ICA, FastICA, and JADE ICA are constructed for the BSS problem in detail and simulations of these algorithms are also exhibited.