Blind separation of second-order nonstationary and temporally colored sources

This paper presents a method of blind source separation that jointly exploits the nonstationarity and temporal structure of sources. The method needs only multiple time-delayed correlation matrices of the observation data, each of which is evaluated at a different time-windowed data frame, to estimate the demixing matrix. We show that the method is quite robust with respect to the spatially correlated but temporally white noise. We also discuss the extension of some existing second-order blind source separation methods. Extensive numerical experiments confirm the validity of the proposed method.