Title :
Identifiability, separability, and uniqueness of linear ICA models
Author :
Eriksson, Jan ; Koivunen, Visa
Author_Institution :
Signal Process. Lab., Helsinki Univ. of Technol., Finland
fDate :
7/1/2004 12:00:00 AM
Abstract :
In this letter, we give the conditions for identifiability, separability and uniqueness of linear real valued independent component analysis (ICA) models. A theorem is formulated and a proof is provided for each of the above concepts. These results extend the conditions for solving ICA problems, originally established by Comon , to wider class of mixing models and source distributions. Examples clarifying the above concepts are presented as well.
Keywords :
blind source separation; identification; independent component analysis; ICA; blind methods; identifiability; independent component analysis; separability; Biomedical signal processing; Blind equalizers; Blind source separation; Data analysis; Independent component analysis; MIMO; Sensor arrays; Signal analysis; Source separation; Wireless communication;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2004.830118
