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—This paper provides insight into the algebraic and geometric structure of Instantaneous Blind Signal Separation based on the assumptions that the cross-correlation functions of the source signals are zero and that the source auto-correlation functions are linearly independent. The presented viewpoint is unifying in the sense that all kinds of statistical(More)
Several blind extraction algorithms have been proposed that extract some signal of interest from a mixture of signals. We propose a novel blind extraction algorithm that extracts the signal that has an autocorrelation closest to a prescribed au-tocorrelation that serves as a mold. Based on the mold we perform a linear transformation of sensor correlation(More)
This paper presents a new and unifying view at multiple-input multiple-output instantaneous blind identification based on the main assumptions that the cross-cumulant functions of the source signals of some arbitrary fixed order vanish for all time tuples and that the source auto-cumulant functions of the same order are linearly independent. Hence, the time(More)
Blind identification is of paramount importance for well-known signal processing problems such as Blind Signal Separation and Direction Of Arrival (DOA) estimation. This paper presents a new method for Multiple-Input Multiple-Output Instantaneous Blind Identification based on second order temporal statistical variabilities in the data, such as non-whiteness(More)
Recently we have shown how a blind source extraction (BSE) algorithm can be equipped with some prior information about mixing parameters of the desired source in order to extract this source. The prior information, which may contain errors, is used to construct a matrix from linear combinations of correlation matrices. The extraction filter is easily(More)
—This paper describes a closed-form solution for 2 × 2 Instantaneous Blind Signal Separation (IBSS) that is based on the exploitation of the non-stationarity of the source signals in an explicit way. Moreover, it is also shown that non-stationarity can be exploited to solve the permutation indeterminacy when it is known that the mixing coefficients satisfy(More)
The emergence of wireless microphones in everyday life creates opportunities to exploit spatial diversity when using fixed microphone arrays combined with these wireless microphones. Traditional array signal processing (ASP) techniques are not suitable for such a scenario since the locations of the wireless sensors are unknown and probably vary over time.(More)