Non-orthogonal joint diagonalization in the least-squares sense with application in blind source separation

IEEE Transactions on Signal Processing

Volumn 50, Issue 7, 2002, Pages 1545-1553

  Yeredor, Arie ^a,b  

^a IEEE   (Israel)

^b TEL AVIV UNIVERSITY   (Israel)

Author keywords

Blind source separation (BSS); Independent component analysis (ICA); Joint diagonalization

Indexed keywords

DIAGONALIZING MATRIX; JOINT DIAGONALIZATION; WEIGHTED LEAST SQUARES;

ADAPTIVE FILTERING; ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; INDEPENDENT COMPONENT ANALYSIS; ITERATIVE METHODS; LEAST SQUARES APPROXIMATIONS; MATRIX ALGEBRA; PARAMETER ESTIMATION; SET THEORY; THEOREM PROVING;

BLIND SOURCE SEPARATION;

EID: 0036648367     PISSN: 1053587X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSP.2002.1011195     Document Type: Article

References (19)

1. Source separation using higher order moments
2. A generalization of joint-diagonalization criteria for source separation
3. Waveform-preserving blind estimation of multiple independent sources
4. Signal processing based on multilinear algebra
5. Independent component analysis and (simultaneous) third-order tensor diagonalization
6. An analytical constant modulus algorithm
7. A blind source separation technique using second-order statistics
8. Blind separation of Gaussian sources via second-order statistics with asymptotically optimal weighting
9. Blind source separation via the second characteristic function
10. Blind source separation of convolved sources by joint approximate diagonalization of cross-spectral density matrices
11. Blind MIMO equalization and joint diagonalization criteria
12. Frequency-domain contrast functions for separation of convolutive mixtures
13. Frequency domain blind MIMO system identification based on second and higher order statistics
14. Jacobi angles for simultaneous diagonalization
15. A least-squares approach to joint diagonalization
16. On the performance of orthogonal source separation algorithms
17. Joint diagonalization via subspace fitting techniques
18. Blind beamforming for non Gaussian signals