| dc.creator | da Costa | |
| dc.creator | Michele N.; Lopes | |
| dc.creator | Renato R.; Romano | |
| dc.creator | Joao Marcos T. | |
| dc.date | 2016 | |
| dc.date | 2017-11-13T13:44:30Z | |
| dc.date | 2017-11-13T13:44:30Z | |
| dc.date.accessioned | 2018-03-29T05:59:09Z | |
| dc.date.available | 2018-03-29T05:59:09Z | |
| dc.identifier | 978-0-9928-6265-7 | |
| dc.identifier | 2016 24th European Signal Processing Conference (eusipco). Ieee, p. 215 - 219, 2016. | |
| dc.identifier | 2076-1465 | |
| dc.identifier | WOS:000391891900043 | |
| dc.identifier | http://ieeexplore.ieee.org/document/7760241/ | |
| dc.identifier | http://repositorio.unicamp.br/jspui/handle/REPOSIP/328784 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1365809 | |
| dc.description | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
| dc.description | This paper presents an algorithm for signal subspace separation in the context of multidimensional data. The proposal is an extension of the randomized Singular Value Decomposition (SVD) for higher-order tensors. From a set derived from random sampling, we construct an orthogonal basis associated with the range of each mode-space of the input data tensor. Multilinear projection of the input data onto each mode-space then transforms the data to a low-dimensional representation. Finally, we compute the Higher-Order Singular Value Decomposition (HOSVD) of the reduced tensor. Furthermore, we propose an algorithm for computing the randomized HOSVD based on the row-extraction technique. The results reveal a relevant improvement from the standpoint of computational complexity. | |
| dc.description | 215 | |
| dc.description | 219 | |
| dc.description | Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP), Brazil [2014/23936-4] | |
| dc.description | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
| dc.description | 24th European Signal Processing Conference (EUSIPCO) | |
| dc.description | AUG 28-SEP 02, 2016 | |
| dc.description | Budapest, HUNGARY | |
| dc.description | | |
| dc.language | English | |
| dc.publisher | IEEE | |
| dc.publisher | New York | |
| dc.relation | 2016 24th European Signal Processing Conference (EUSIPCO) | |
| dc.rights | fechado | |
| dc.source | WOS | |
| dc.subject | Higher-order Singular Value Decomposition | |
| dc.subject | Randomized Algorithm | |
| dc.subject | Signal Subspace Method | |
| dc.subject | Tensor Decomposition | |
| dc.subject | Dimension Reduction | |
| dc.subject | Row-extraction Technique | |
| dc.title | Randomized Methods For Higher-order Subspace Separation | |
| dc.type | Actas de congresos | |
