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期刊名:Siam journal on matrix analysis and applications

缩写:SIAM J MATRIX ANAL A

ISSN:0895-4798

e-ISSN:1095-7162

IF/分区:2.6/Q1

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共收录本刊相关文章索引6
Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Joshua Pickard,Can Chen,Cooper Stansbury et al. Joshua Pickard et al.
Hypergraphs and tensors extend classic graph and matrix theory to account for multiway relationships, which are ubiquitous in engineering, biological, and social systems. While the Kronecker product is a potent tool for analyzing the coupli...
Jacqueline Wentz,Jeffrey C Cameron,David M Bortz Jacqueline Wentz
We present the analytical singular value decomposition of the stoichiometry matrix for a spatially discrete reaction-diffusion system. The motivation for this work is to develop a matrix decomposition that can reveal hidden spatial flux pat...
Joong-Ho Won,Hua Zhou,Kenneth Lange Joong-Ho Won
This paper studies the problem of maximizing the sum of traces of matrix quadratic forms on a product of Stiefel manifolds. This orthogonal trace-sum maximization (OTSM) problem generalizes many interesting problems such as generalized cano...
Ariel Jaffe,Roi Weiss,Boaz Nadler Ariel Jaffe
Real eigenpairs of symmetric tensors play an important role in multiple applications. In this paper we propose and analyze a fast iterative Newton-based method to compute real eigenpairs of symmetric tensors. We derive sufficient conditions...
Ilse C F Ipsen,Hua Zhou Ilse C F Ipsen
Probabilistic models are proposed for bounding the forward error in the numerically computed inner product (dot product, scalar product) between two real n-vectors. We derive probabilistic perturbation bounds as well as probabilistic roundo...
Erik Thiede,Brian VAN Koten,Jonathan Weare Erik Thiede
For many Markov chains of practical interest, the invariant distribution is extremely sensitive to perturbations of some entries of the transition matrix, but insensitive to others; we give an example of such a chain, motivated by a problem...