Konferenční příspěvek

Tichavský P., Doron E., Yeredor A., Nielsen J.

Proceedings of 14th European Signal Processing Conference (EUSIPCO 2006).

EURASIP

Florence

2006

1-5

Ing. Petr Tichavský, CSc. (ÚTIA - Oddělení stochastické informatiky)

independent component analysis, blind source separation

1568981867 [file]

The second-order blind identification (SOBI) algorithm for separation of stationary sources was proved to be useful in many biomedical applications. This paper revisits the so called weights-adjusted variant of SOBI, known as WASOBI, which is asymptotically optimal (in separating Gaussian parametric processes), yet prohibitively computationally demanding for more than 2-3 sources. A computationally feasible implementation of the algorithm is proposed, which has a complexity of the same order as SOBI. Excluding the estimation of the correlation matrices, the post-processing complexity of SOBI is $O(d^4M)$, where $d$ is the number of the signal components and $M$ is the number of covariance matrices involved. The additional complexity of our proposed implementation of WASOBI is $O(d^6+d^3M^3)$ operations. However, for WASOBI, the number $M$ of the matrices can be significantly lower than that of SOBI without compromising performance. WASOBI is shown to significantly outperform SOBI in simulation, and can be applied, e.g., in the processing of low density EEG signals.