Results 71 to 80 of about 1,468 (179)

Application of semidefinite programming to truss design optimization / Santvaros optimizavimo uždavinių sprendimas taikant pusiau apibrėžtą programavimą

Mokslas: Lietuvos Ateitis, 2015
Semidefinite Programming (SDP) is a fairly recent way of solving optimization problems which are becoming more and more important in our fast moving world. It is a minimization of linear function over the intersection of the cone of positive semidefinite
Rasa Giniūnaitė
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Singular Values of Differences of Positive Semidefinite Matrices [PDF]

SIAM Journal on Matrix Analysis and Applications, 2001
Based on known results, the author shows relations between the singular values of two positive semidefinite matrices. Let \(A\) and \(B\) be complex positive semidefinite matrices of order \(n\) and let us denote as \(A \oplus B\) the block diagonal matrix with \(A\) and \(B\) on the diagonal. Using the common notation for singular values \(s_1(.) \geq
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Disjoint sections of positive semidefinite matrices and their applications in linear statistical models

Special Matrices
Given matrices AA and BB of the same order, AA is called a section of BB if R(A)∩R(B−A)={0}{\mathscr{R}}\left(A)\cap {\mathscr{R}}\left(B-A)=\left\{0\right\} and R(AT)∩R((B−A)T)={0}{\mathscr{R}}\left({A}^{T})\cap {\mathscr{R}}\left({\left(B-A)}^{T ...
Eagambaram N.
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Mixed discriminants of positive semidefinite matrices

Linear Algebra and its Applications, 1989
If \(A^ k=(a^ k_{ij})\) are \(n\times n\) complex matrices \(k=1,2,...,n\), then their mixed discriminant \(D(A^ 1,...,A^ n)\) is \(\frac{1}{n!}\sum_{\sigma \in S_ n}\det (a_{ij}^{\sigma (j)})\), where \(S_ n\) is the symmetric group of degree n. If all the \(A^ k\) are equal this turns out to be det A, whereas if each \(A^ k\) is a diagonal matrix the
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Semidefinite Programming Approaches to Hankel Matrix Approximation and Completion via Primal–Dual Interior-Point Methods

Journal of Mathematics
Data completion techniques offer numerous advantages in various fields. However, completing large datasets that must satisfy specific criteria can be challenging, necessitating the use of approximative completion methods.
Hajar A. Alshaikh, Mohammed M. Alshahrani, Suliman S. Al-Homidan   +2 more
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Operational Choices for Risk Aggregation in Insurance: PSDization and SCR Sensitivity

Risks, 2018
This work addresses crucial questions about the robustness of the PSDization process for applications in insurance. PSDization refers to the process that forces a matrix to become positive semidefinite.
Xavier Milhaud, Victorien Poncelet, Clement Saillard   +2 more
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Weighted Algebraic Connectivity Maximization for Optical Satellite Networks

IEEE Access, 2017
In this paper, the topology configuration methods for heterogeneous optical satellite networks are investigated. Our objectives are to maximize weighted algebraic connectivity with respect to both network initialization and reconfiguration scenarios ...
Yongxing Zheng, Shanghong Zhao, Yun Liu, Yongjun Li, Qinggui Tan, Ning Xin   +5 more
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Some inequalities for unitarily invariant norms of matrices

Journal of Inequalities and Applications, 2011
This article aims to discuss inequalities involving unitarily invariant norms. We obtain a refinement of the inequality shown by Zhan. Meanwhile, we give an improvement of the inequality presented by Bhatia and Kittaneh for the Hilbert-Schmidt norm ...
Wang Shaoheng, Zou Limin, Jiang Youyi
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A Generalized HSS Iteration Method for Continuous Sylvester Equations

Journal of Applied Mathematics, 2014
Based on the Hermitian and skew-Hermitian splitting (HSS) iteration technique, we establish a generalized HSS (GHSS) iteration method for solving large sparse continuous Sylvester equations with non-Hermitian and positive definite/semidefinite matrices ...
Xu Li, Yu-Jiang Wu, Ai-Li Yang, Jin-Yun Yuan   +3 more
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On permanents of positive semidefinite matrices

Linear Algebra and its Applications, 1985
Let A and B be positive semidefinite real symmetric matrices. Using properties of tensor products, \textit{T. Ando} [Hokkaido Math. J. 10, Special Issue, 10, No.1, 18-36 (1981; Zbl 0484.15006)] proved that \(per(A+B)\geq per A+per B\). In this paper, it is shown that the Binet- Cauchy formula for the permanent of a product of matrices can also be used ...
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