Blind Separation of Sources Using Temporal Correlation of the Observed Signals

Kiyotoshi MATSUOKA
Masahiro OYA

IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E80-A       pp.695-704
Publication Date: 1997/04/25
Online ISSN: 
Print ISSN: 0916-8508
Type of Manuscript: Category: Digital Signal Processing
blind separation,  stationary signals,  temporal correlation,  second-order statistics,  

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This paper proposes a new method for recovering the original signals from their linear mixtures observed by the same number of sensors. It is performed by identifying the linear transform from the sources to the sensors, only using the sensor signals. The only assumption of the source signals is basically the fact that they are statistically mutually independent. In order to perform the 'blind' identification, some time-correlational information in the observed signals are utilized. The most important feature of the method is that the full information of available time-correlation data (second-order statistics) is evaluated, as opposed to the conventional methods. To this end, an information-theoretic cost function is introduced, and the unknown linear transform is found by minimizing it. The propsed method gives a more stable solution than the conventional methods.