Studies on Estimation of the Sources Number in Blind Source Separation Problems
Takaaki Ishibashi, Katsuhiro Inoue, Hiromu Gotanda, Kousuke Kumamaru · 2006 SICE-ICASE International Joint Conference · 2006
ICA (Independent Component Analysis) can separate unknown source signals from their mixture signals without information on the transfer functions, provided that the sources are statistically independent. When the number of the source signals is equal to that of the observed signals, the original sources can be recovered except for indeterminacy of scale and permutation. However, the number of the sources is unknown in a real environment. In this paper, we propose an estimation method for the number of the sources based on the joint distribution of the observed signals under two-sensor configuration. From several simulation results, it is found that the number of the sources is coincident to that of peaks in the histogram of the distribution