Block Jacobi-type methods for non-orthogonal joint diagonalisation

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2009, Pages 3285-3288

  Shen, Hao ^a   Hüper, Knut ^b  

^a TECHNICAL UNIVERSITY OF MUNICH   (Germany)

^b UNIVERSITY OF WÜRZBURG   (Germany)

Author keywords

Block Jacobi type method; Independent component analysis (ICA); Local quadratic convergence; Nonorthogonal joint diagonalisation (NoJD); Oblique manifold

Indexed keywords

BLOCK JACOBI-TYPE METHOD; LOCAL QUADRATIC CONVERGENCE; LOG-LIKELIHOOD FUNCTIONS; NONORTHOGONAL JOINT DIAGONALISATION (NOJD); NUMERICAL EXPERIMENTS; OBLIQUE MANIFOLD; RIGOROUS ANALYSIS; SYMMETRIC MATRICES; TYPE METHODS;

ACOUSTICS; COST FUNCTIONS; HEMODYNAMICS; NUMERICAL METHODS; SIGNAL PROCESSING;

INDEPENDENT COMPONENT ANALYSIS;

EID: 70349202095     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2009.4960326     Document Type: Conference Paper

References (12)

1. P.-A. Absil and K. A. Gallivan, "Joint diagonalization on the oblique manifold for independent component analysis," in Proceedings of ICASSP 2006, pp. V945-V948.
2. B. Afsari, "Simple LU and QR based non-orthogonal matrix joint diagonalization," in Lecture Notes in Computer Science, Proceedings of ICA 2006, vol. 3889, pp. 1-7.
3. B. Afsari, "Sensitivity analysis for the problem of matrix joint diagonalization," SIAM Journal on Matrix Analysis and Applications, vol. 30, pp. 1148-1171, 2008.
4. J.-F. Cardoso, "On the performance of orthogonal source separation algorithms," in Proceedings of EUSIPCO 1994, pp. 776-779.
5. P. Comon, "Independent component analysis, a new concept?," Signal Processing, vol. 36, no. 3, pp. 287-314, 1994.
6. K. Hüper, "A dynamical system approach to matrix eigenvalue algorithms," in the IMA Volumes in Mathematics and its Applications, Mathematical Systems Theory in Biology, Communications, Computation, vol. 134, pp. 257-274, 2003.
7. M. Joho and K. Rahbar, "Joint diagonalization of correlation matrices by using Newton methods with application to blind signal separation," in Proceedings of SAM 2002, pp. 403-407.
8. D. T. Pham, "Joint approximate diagonalization of positive definite Hermitianmatrices," SIAMJournal on Matrix Analysis and Applications, vol. 22, pp. 1136-1152, 2001.
9. H. Shen, M. Kleinsteuber, and K. Hüper, "Block Jacobi-type methods for log-likelihood based linear independent subspace analysis," in Proceedings of MLSP 2007, pp. 133-138.
10. A.-J. van der Veen, "Joint diagonalization via subspace fitting techniques," in Proceedings of ICASSP 2001, pp. 2773-2776.
11. F. Wang, Z. Liu, and J. Zhang, "Nonorthogonal joint diagonalization algorithm based on trigonometric parameterization," IEEE Transactions on Signal Processing, vol. 55, no. 11, pp. 5299-5308, 2007.
12. A. Yeredor, "Non-orthogonal joint diagonalization in the leastsquares sense with application in blind source separation," IEEE Transactions on Signal Processing, vol. 50, no. 7, pp. 1545-1553, 2002.