eprintid: 3031
rev_number: 13
eprint_status: archive
userid: 17
dir: disk0/00/00/30/31
datestamp: 2018-06-18 08:05:15
lastmod: 2018-12-17 19:26:58
status_changed: 2018-12-17 19:26:58
type: article
metadata_visibility: show
creators_name: Le, Trung Thanh
creators_name: Nguyen, Viet Dung
creators_name: Nguyen, Linh Trung
creators_name: Abed-Meraim, Karim
creators_id: letrungthanhtbt@gmail.com
creators_id: nvdung@vnu.edu.vn
creators_id: linhtrung@vnu.edu.vn
creators_id: karim.abed-meraim@univ-orleans.fr
title: Three-Way Tensor Decompositions: A Generalized Minimum Noise Subspace Based Approach
ispublished: pub
subjects: ECE
divisions: avitech
divisions: fac_fet
abstract: Tensor decomposition has recently become a popular method of multi-dimensional data analysis in various applications. The main interest in tensor decomposition is for dimensionality reduction, approximation or subspace purposes. However, the emergence of “big data” now gives rise to increased computational complexity for performing tensor decomposition. In this paper, motivated by the advantages of the generalized minimum noise subspace (GMNS) method, recently proposed for array processing, we proposed two algorithms for principal subspace analysis (PSA) and two algorithms for tensor decomposition using parallel factor analysis (PARAFAC) and higher-order singular value decomposition (HOSVD). The proposed decomposition algorithms can preserve several desired properties of PARAFAC and HOSVD while substantially reducing the computational complexity. Performance comparisons of PSA and tensor decomposition of our proposed algorithms against the state-of-the-art ones were studied via numerical experiments. Experimental results indicated that the proposed algorithms are of practical values.
date: 2018-06-15
date_type: published
publisher: REV
official_url: http://rev-jec.org
id_number: http://dx.doi.org/10.21553/rev-jec.196
contact_email: linhtrung@vnu.edu.vn
full_text_status: public
publication: REV Journal on Electronics and Communications
volume: 8
number: 1-2
pagerange: 14-31
refereed: TRUE
issn: 1859-378X
citation:   Le, Trung Thanh and Nguyen, Viet Dung and Nguyen, Linh Trung and Abed-Meraim, Karim  (2018) Three-Way Tensor Decompositions: A Generalized Minimum Noise Subspace Based Approach.  REV Journal on Electronics and Communications, 8  (1-2).   pp. 14-31.  ISSN 1859-378X     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3031/1/196_LTThanh_preprint.pdf