Results 31 to 40 of about 145,037 (166)
Computing the Polar Decomposition and the Matrix Sign Decomposition in Matrix Groups [PDF]
SIAM Journal on Matrix Analysis and Applications, 2004 The polar decomposition of \(A\) is \(A=UH\), where \(A\) has complex elements, \(U\) is unitary, \(H\) is Hermitian positive semi-definite. The authors identify a family of globally convergent rational iterations that preserve group structure. They show how the structure preservation leads to particularly convenient convergence tests in the case of ...
Higham, Nicholas J. +3 more
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Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition. [PDF]
IEEE J Sel Top Signal Process, 2016 Ong F, Lustig M.
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A Theoretical Question in the Optimal Design of Matrix Decomposition Based FIR Filter
IEEE Access, 2020 The matrix decomposition (MD) based finite impulse response (FIR) filter is a low-complexity FIR filter. It has been tested the coefficients of the MD-FIR filter can be effectively optimized by the trust-region-iterative-gradient-searching (TR-IGS ...
Hao Wang +3 more
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A new integrated framework for the identification of potential virus–drug associations
Frontiers in Microbiology, 2023 IntroductionWith the increasingly serious problem of antiviral drug resistance, drug repurposing offers a time-efficient and cost-effective way to find potential therapeutic agents for disease.
Jia Qu +4 more
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Jordan Matrix Decomposition [PDF]
Formalized Mathematics, 2008 We follow the rules: i, j, m, n, k denote natural numbers, K denotes a field, and a, λ denote elements of K. Let us consider K, λ, n. The Jordan block of λ and n yields a matrix over K and is defined by the conditions (Def. 1). (Def. 1)(i) len (the Jordan block of λ and n) = n, (ii) width (the Jordan block of λ and n) = n, and (iii) for all i, j such ...
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Guided Semi-Supervised Non-Negative Matrix Factorization
Algorithms, 2022 Classification and topic modeling are popular techniques in machine learning that extract information from large-scale datasets. By incorporating a priori information such as labels or important features, methods have been developed to perform ...
Pengyu Li +6 more
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Numerical Matrix Decomposition
, 2021 In 1954, Alston S. Householder published \textit{Principles of Numerical Analysis}, one of the first modern treatments on matrix decomposition that favored a (block) LU decomposition-the factorization of a matrix into the product of lower and upper triangular matrices.
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The Journal of Engineering, 2017 Based on the vectorised and cache optimised kernel, a parallel lower upper decomposition with a novel communication avoiding pivoting scheme is developed to solve dense complex matrix equations generated by the method of moments.
Yan Chen +4 more
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Randomized Rank-Revealing QLP for Low-Rank Matrix Decomposition
IEEE Access, 2023 The pivoted QLP decomposition is computed through two consecutive pivoted QR decompositions. It is an approximation to the computationally prohibitive singular value decomposition (SVD). This work is concerned with a partial QLP decomposition of matrices
Maboud F. Kaloorazi +4 more
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A System of Four Generalized Sylvester Matrix Equations over the Quaternion Algebra
MathematicsIn this paper, we make use of the simultaneous decomposition of eight quaternion matrices to study the solvability conditions and general solutions to a system of two-sided coupled Sylvester-type quaternion matrix equations AiXiCi+BiXi+1Di=Ωi,i=1,2,3,4 ...
Zhuo-Heng He, Jie Tian, Shao-Wen Yu
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