Blind separation of instantaneous mixtures of nonstationary sources

IEEE Transactions on Signal Processing

Volumn 49, Issue 9, 2001, Pages 1837-1848

  Pham, Dinh Tuan ^a,b   Cardoso, Jean François ^a,b  

^a IEEE   (France)

^b CNRS   (France)

Author keywords

Blind source separation; Independent component analysis; Joint diagonalization; Maximum likelihood; Mutual information; Nonstationarity

Indexed keywords

NONSTATIONARY SOURCES;

INDEPENDENT COMPONENT ANALYSIS; MATHEMATICAL MODELS; MATRIX ALGEBRA; MAXIMUM LIKELIHOOD ESTIMATION; VECTORS;

BLIND SOURCE SEPARATION;

EID: 0035448026     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/78.942614     Document Type: Article

References (22)

1. Blind signal separation: Statistical principles
2. Independent component analysis: A new concept?
3. Blind separation of mixture of independent sources through a quasimaximum likelihood approach
4. AMUSE: A new blind identification algorithm
5. A blind source separation technique based on second order statistics
6. Blind source detection and separation using second order nonstationarity
7. Source separation using second order statistics: Identifiability conditions and algorithms
8. A neural net for blind separation of nonstationary signals
9. Adaptive blind separation of audio sources by a physically compact device using second-order statistics
10. Convolutive blind source separation of nonstationary sources
11. Equivariant adaptive source separation
12. Differential-geometrical methods in statistics
13. Elements of information theory
14. Blind beamforming for non Gaussian signals
15. On the performance of orthogonal source separation algorithms
16. Joint approximate diagonalization of positive definite Hermitian matrices
17. An algorithm for the simultaneous orthogonal transformation of several positive definite symmetric matrices to nearly orthogonal form
18. Natural gradient works efficiently in learning
19. Separation of nonstationary natural signals