scholarly journals Three-Way Tensor Decompositions: A Generalized Minimum Noise Subspace Based Approach

2018 ◽  
Author(s):  
Le Trung Thanh ◽  
Viet-Dung Nguyen ◽  
Nguyen Linh-Trung ◽  
Karim Abed-Meraim
Keyword(s):  
Computational Complexity ◽  
State Of The Art ◽  
Tensor Decomposition ◽  
Decomposition Algorithms ◽  
Subspace Analysis ◽  
Tensor Decompositions ◽  
Noise Subspace ◽  
Parallel Factor ◽  
Value Decomposition ◽  
Minimum Noise

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.

scholarly journals Generalized Minimum Noise Subspace For Array Processing

2017 ◽  
Vol 65 (14) ◽  
pp. 3789-3802 ◽  
Author(s):  
Viet-Dung Nguyen ◽  
Karim Abed-Meraim ◽  
Nguyen Linh-Trung ◽  
Rodolphe Weber
Keyword(s):  
Array Processing ◽  
Noise Subspace ◽  
Minimum Noise

scholarly journals Blind system identification using minimum noise subspace

1997 ◽  
Vol 45 (3) ◽  
pp. 770-773 ◽  
Author(s):  
Yingbo Hua ◽  
K. Abed-Meraim ◽  
M. Wax
Keyword(s):  
System Identification ◽  
Noise Subspace ◽  
Blind System Identification ◽  
Minimum Noise

Estimation of the Number of Signal Components Based on Singular Values of Noise Subspace

2011 ◽  
Vol 33 (9) ◽  
pp. 2039-2044 ◽  
Author(s):  
Xin-peng Zhou ◽  
Feng Han ◽  
Guo-hua Wei ◽  
Si-liang Wu
Keyword(s):  
Singular Values ◽  
Noise Subspace

Modeling perturbation of scattering coefficients by using dominating noise subspace

2020 ◽  
Author(s):  
Terence H. Chan ◽  
Wenqi Zhang ◽  
Sander Wahls ◽  
Alan Pak Tao Lau ◽  
V. Shahraam Afshar
Keyword(s):  
Scattering Coefficients ◽  
Noise Subspace
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