Results 11 to 20 of about 6,368,085 (214)
Computing a nearest symmetric positive semidefinite matrix [PDF]
Linear Algebra and its Applications, 1988 The problem of computing a nearest positive semidefinite matrix (notation used \(X\geq 0)\) to an arbitrary real matrix A is considered. The criterion of approximation is the distance \(\delta (A)=\min_{X=X^ T\geq 0}\| A-X\|\) where the norm is chosen to be either Frobenius or 2-norm. The paper consists of two parts. In the first part the author proves
Higham, Nicholas J.
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Positive semidefinite matrix completions on chordal graphs and constraint nondegeneracy in semidefinite programming [PDF]
Linear Algebra and its Applications, 2009 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qi, Houduo
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Applied Set-Valued Analysis and Optimization, 2023 We present an algorithm for computing the minimum-rank positive semidefinite completion of a sparse matrix with a chordal sparsity pattern. This problem is tractable, in contrast to the minimum-rank positive semidefinite completion problem for general sparsity patterns.
Jiang, Xin +3 more
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Binary positive semidefinite matrices and associated integer polytopes [PDF]
, 2012 We consider the positive semidefinite (psd) matrices with binary entries, along with the corresponding integer polytopes.We begin by establishing some basic properties of these matrices and polytopes.
Sorensen, M M, Letchford, A N
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The complete positivity of symmetric tridiagonal and pentadiagonal matrices
Special Matrices, 2022 We provide a decomposition that is sufficient in showing when a symmetric tridiagonal matrix AA is completely positive. Our decomposition can be applied to a wide range of matrices.
Cao Lei, McLaren Darian, Plosker Sarah
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The Complexity of Positive Semidefinite Matrix Factorization [PDF]
SIAM Journal on Optimization, 2017 11 ...
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Positive Semidefinite Matrix Factorization Based on Truncated Wirtinger Flow [PDF]
2020 28th European Signal Processing Conference (EUSIPCO), 2021 This paper deals with algorithms for positive semidefinite matrix factorization (PSDMF). PSDMF is a recently-proposed extension of nonnegative matrix factorization with applications in combinatorial optimization, among others. In this paper, we focus on improving the local convergence of an alternating block gradient (ABC) method for PSDMF in a noise ...
Lahat, Dana, Févotte, Cédric
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Analysis of Fixing Nodes Used in Generalized Inverse Computation
Advances in Electrical and Electronic Engineering, 2014 In various fields of numerical mathematics, there arises the need to compute a generalized inverse of a symmetric positive semidefinite matrix, for example in the solution of contact problems.
Pavla Hruskova
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On (conditional) positive semidefiniteness in a matrix-valued context [PDF]
Studia Mathematica, 2017 43 pages, replaced Example 4.19 (i) (the original version contained a mistake); journal reference ...
Gesztesy, Fritz, Pang, Michael
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Sufficient conditions to be exceptional
Special Matrices, 2016 A copositive matrix A is said to be exceptional if it is not the sum of a positive semidefinite matrix and a nonnegative matrix. We show that with certain assumptions on A−1, especially on the diagonal entries, we can guarantee that a copositive matrix A
Johnson Charles R., Reams Robert B.
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