Results 321 to 330 of about 3,813,510 (369)

3D diffraction imaging method using low-rank matrix decomposition

, 2020
Seismic weak responses from subsurface small-scale geologic discontinuities or inhomogeneities are encoded in 3D diffractions. Separating weak diffractions from a strong reflection background is a difficult problem for diffraction imaging, especially for
Jingtao Zhao, Caixia Yu, S. Peng, Chuangjian Li   +3 more
semanticscholar   +1 more source

On the cartesian decomposition of a matrix

Linear and Multilinear Algebra, 1985
The main result of this paper is the following Let A and B be n×n hermitian matrices with eigenvalues respectively, ordered so that and let M1 be any k×k principal submatrix of . Necessary and sufficient conditions for equality are given.
António Leal Duarte, João Filipe Queiró   +1 more
openaire   +2 more sources

Wavelet-Integrated Alternating Sparse Dictionary Matrix Decomposition in Thermal Imaging CFRP Defect Detection

IEEE Transactions on Industrial Informatics, 2019
With the increasing importance of using carbon fiber reinforced polymer (CFRP) composite in the aircraft industry, it becomes ever more critical to monitor the quality and health of CFRP during the manufacturing process as well as the in-service ...
Junaid Ahmed, B. Gao, W. L. Woo
semanticscholar   +1 more source

Structural analysis by matrix decomposition

Journal of the Franklin Institute, 1968
Abstract A physical interpretation is derived for the Choleski decomposition method as applied to structural analysis. Both the stiffness (displacement) and flexibility (force) methods of structural analysis are treated. The interpretation is shown to be valuable in providing physically meaningful upper and lower bounds on the elements of the ...
Moshe F. Rubinstein, Richard Rosen
openaire   +3 more sources

On LU decomposition of a centrosymmetric matrix

Information Sciences, 1992
An \(LU\) decomposition of a centrosymmetric matrix, the Choleski decomposition of a centrosymmetric, symmetric and positively defined matrix, as well as algorithms for finding the inverse of such a matrix by using this decomposition are presented in the paper.
K. Venkata Ramana, Ivatury Ramabhadrasarma, A. V. Dattatreya Rao   +2 more
openaire   +3 more sources

GoDec+: Fast and Robust Low-Rank Matrix Decomposition Based on Maximum Correntropy

IEEE Transactions on Neural Networks and Learning Systems, 2018
GoDec is an efficient low-rank matrix decomposition algorithm. However, optimal performance depends on sparse errors and Gaussian noise. This paper aims to address the problem that a matrix is composed of a low-rank component and unknown corruptions.
K. Guo, L. Liu, Xiangmin Xu, Dong Xu, D. Tao   +4 more
semanticscholar   +1 more source

Freeness and matrix decompositions

Science China Mathematics, 2011
If a semicircular element and the diagonal subalgebra of a matrix algebra are free in a finite von Neumann algebra (with respect to a normal trace), then, up to the conjugation by a diagonal unitary element, all entries of the semicircular element are uniquely determined in the sense of (joint) distribution.
Junhao Shen, Liming Ge, Liming Ge
openaire   +2 more sources

Bio‐SCOPE: fast biexponential T1ρ mapping of the brain using signal‐compensated low‐rank plus sparse matrix decomposition

Magnetic Resonance in Medicine, 2019
To develop and evaluate a fast imaging method based on signal‐compensated low‐rank plus sparse matrix decomposition to accelerate data acquisition for biexponential brain T1ρ mapping (Bio‐SCOPE).
Yanjie Zhu, Yuanyuan Liu, L. Ying, Xin Liu, Hairong Zheng, D. Liang   +5 more
semanticscholar   +1 more source

A decomposition for in-place matrix transposition [PDF]

Proceedings of the 19th ACM SIGPLAN symposium on Principles and practice of parallel programming, 2014
We describe a decomposition for in-place matrix transposition, with applications to Array of Structures memory accesses on SIMD processors. Traditional approaches to in-place matrix transposition involve cycle following, which is difficult to parallelize, and on matrices of dimension m by n require O(mn log mn) work when limited to less than O(mn ...
KellerAlexander, CatanzaroBryan, GarlandMichael   +2 more
openaire   +2 more sources

Stability analysis by matrix decomposition

Journal of the Franklin Institute, 1970
Abstract A method is presented for the stability analysis of structures using a combination of matrix iteration and matrix decomposition. The method is extented to stability analysis of structures in which two critical loads are present whose absolute values are relatively close or identical.
Lawrence D. Hofmeister, Lewis P. Felton, Moshe F. Rubinstein   +2 more
openaire   +3 more sources