DocumentCode
178679
Title
Error Analysis of low-rank three-way tensor factorization approach to blind source separation
Author
Kopriva, Ivica ; Royer, Jean-Philip ; Thirion-moreau, Nadege ; Comon, Pierre
Author_Institution
Div. for Laser & Atomic R&D, Ruder Boskovic Inst., Zagreb, Croatia
fYear
2014
fDate
4-9 May 2014
Firstpage
3186
Lastpage
3190
Abstract
In tensor factorization approach to blind separation of multidimensional sources two formulas for calculating the source tensor have emerged. In practice, it is observed that these two schemes exhibit different levels of robustness against perturbations of the factors involved in the tensor model. Motivated by both practical reasons and the will to better figure this out, we present error analyses in source tensor estimation performed by low-rank factorization of three-way tensors. To that aim, computer simulations as well as the analytical calculation of the theoretical error are carried out. The conclusions drawn from these numerical and analytical error analyses are supported by the results obtained thanks to the tensor factorization based blind decomposition of an experimental multispectral image of a skin tumor.
Keywords
blind source separation; error analysis; matrix decomposition; medical image processing; skin; tensors; tumours; analytical error analyses; blind decomposition; blind source separation; error analysis; low-rank three-way tensor factorization approach; multidimensional sources; multispectral image; numerical error analyses; skin tumor; source tensor estimation; theoretical error; Analytical models; Error analysis; Loading; Matrix decomposition; Noise; Numerical models; Tensile stress; Tensor models; blind source separation; multidimensional signal;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6854188
Filename
6854188
Link To Document