Title :
Separation of independent sources from correlated inputs
Author :
Lacoume, J.L. ; Ruiz, P.
Author_Institution :
CEPHAG, ENSIEG, St. Martin d´´Heres, France
fDate :
12/1/1992 12:00:00 AM
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;
Journal_Title :
Signal Processing, IEEE Transactions on