Three-mode data set analysis using higher order subspace method: Application to sonar and seismo-acoustic signal processing

Signal Processing

Volumn 84, Issue 5, 2004, Pages 919-942

  Le Bihan, Nicolas ^a   Ginolhac, Guillaume ^b  

^a ENSIEG   (France)

^b GEA   (France)

Author keywords

Acoustic and elastic wavefield separation; Higher order singular value decomposition; Multimodal sonar images; Seismo acoustic signal processing; Subspace method; Three mode array decomposition; Three mode arrays; Three mode PCI; Wave separation

Indexed keywords

AEROSPACE APPLICATIONS; DATA REDUCTION; MATRIX ALGEBRA; SEISMIC WAVES; SEISMOLOGY; SONAR;

SUBSPACE METHODS; THREE-MODE ARRAY DECOMPOSITION; WAVE SEPARATION;

SIGNAL PROCESSING;

EID: 1842529867     PISSN: 01651684     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.sigpro.2004.02.003     Document Type: Article

References (20)

1. R. Bro, Multi-way analysis in the food industry, Models, algorithms and applications, Ph.D. Thesis, University of Amsterdam, 1998.
2. P. Comon, Tensors decompositions, State of the art and applications, IMA Conference of Mathematics in Signal Processing, Warwick, UK, December 18-20, 2000.
3. De Lathauwer L., De Moor B., Vandewalle J. A multilinear singular value decomposition. SIAM J. Matrix Anal. Appl. 21(4):2000;1253-1278.
4. Eckart C., Young G. The approximation of one matrix by another one of lower rank. Psychometrica. 1:1936;211-218.
5. Ginolhac G., Jourdain G. Principal component inverse algorithm for detection in presence of reverberation. IEEE J. Ocean. Eng. 27(2):April 2002;310-321.
6. Glangeaud F., Mari J.-L., Lacoume J.-L., Mars J., Nardin M. Dispersive seismic wave tools in geophysics. Eur. J. Environ. Eng. Geophys. 3:1999;265-306.
7. Golub G.H., Van Loan C.F. Matrix Computation. 1989;Johns Hopkins University Press, Baltimore, MD.
8. Håstad J. Tensor rank is NP-complete. J. Algorithms. 11:1990;644-654.
9. Kirsteins I.P., Tufts D.W. Adaptative detection using low rank approximation to a data matrix. IEEE Trans. Aerospace Electron. Systems. 30(1):1994;55-67.
10. Kroonenberg P.M. Three-mode Principal Component Analysis. 1983;DSWO Press, Leiden.
11. Kruskal J.B. Three-way arrays: rank and uniqueness of trilinear decompositions, with applications to arithmetic complexity and statistics. Linear Algebra Appl. 18:1977;95-138.
12. Kumaresan R., Kirsteins I.P., Tufts D.W. Data adaptive signal estimation by singular value decomposition of a data matrix. Proc. IEEE. 70(6):June 1982;684-685.
13. N. Le Bihan, Linear and multilinear processing of vector signals, Application to seismic wave separation, Ph.D. Thesis, INPG, 2001.
14. N. Le Bihan, G. Ginolhac, Subspace method for 3D arrays, Second Workshop on Physics in Signal and Image Processing (PSIP), Marseille, France, 2000.
15. MacBeth C., Xiang-Yang L. Linear matrix operations for multicomponent seismic processing. Geophys. J. Int. 124:1996;189-208.
16. Nehorai A., Paldi E. Vector-sensor array processing for electromagnetic source localization. IEEE Trans. Signal Process. 42(2):1994;376-398.
17. Scharf L.L. Statistical Signal Processing. 1991;Addison-Wesley, Reading, MA.
18. Sidiropoulos N.D., Bro R., Giannakis G.B. Parallel factor analysis in sensor array processing. IEEE Trans. Signal Process. 48(8):2000;2377-2388.
19. Sidiropoulos N.D., Giannakis G.B., Bro R. Blind PARAFAC receivers for DS-CDMA systems. IEEE Trans. Signal Process. 48(3):2000;810-823.
20. Tucker L.R. Some mathematical notes on three-mode factor analysis. Psychometrics. 31:1966;279-311.