Separation of independent sources from correlated inputs

Author

Lacoume, J.L. ; Ruiz, P.

Author_Institution

CEPHAG, ENSIEG, St. Martin d´´Heres, France

Volume

40

Issue

12

fYear

1992

fDate

12/1/1992 12:00:00 AM

Firstpage

3074

Lastpage

3078

Abstract

The characterization of independent stationary stochastic components (sources), is generally achieved by using the spectral matrix of partially correlated measurements, which are linearly related to the components of interest. In the general case where no assumptions are made concerning the way the sources are mixed on the measurements, the spectral matrix is not able to extract the true sources. While spectral analysis only uses second-order properties of independent stochastic sources, a procedure based on higher-order analysis (fourth-order cross cumulants) is developed. This approach leads to a complete identification of the sources

Keywords

correlation methods; spectral analysis; statistical analysis; stochastic processes; correlated inputs; fourth-order cross cumulants; higher order statistics; higher-order analysis; independent stochastic sources; partially correlated measurements; spectral analysis; spectral matrix; stationary stochastic components; Array signal processing; Discrete Fourier transforms; Frequency; Higher order statistics; Independent component analysis; Matrix decomposition; Signal processing algorithms; Spectral analysis; Stochastic processes; Working environment noise;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.175753

Filename

175753