Title :
Contrast Functions for Non-circular and Circular Sources Separation in Complex-Valued ICA
Author :
Chen, Zhe ; Ma, Jinwen
Author_Institution :
RIKEN Brain Sci. Inst., Saitama
Abstract :
In this paper, the complex-valued ICA problem is studied in the context of blind complex-source separation. We formulate the complex ICA problem in a general setting, and define the superadditive functional that may be used for constructing a contrast function for circular complex sources separation. We propose several contrast functions and study their properties. Finally, we also discuss relevant issues and present the convex analysis of a specific contrast function.
Keywords :
blind source separation; functions; independent component analysis; matrix algebra; blind complex-source separation; circular sources separation; complex-valued ICA problem; contrast functions; convex analysis; matrix algebra; noncircular source separation; Biological neural networks; Covariance matrix; Decorrelation; Eigenvalues and eigenfunctions; Image processing; Independent component analysis; Random variables; Signal processing; Signal processing algorithms; Statistics;
Conference_Titel :
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9490-9
DOI :
10.1109/IJCNN.2006.246718