Results 11 to 20 of about 198,875 (210)
First-order Perturbation Theory for Eigenvalues and Eigenvectors [PDF]
SIAM Review, 2019 We present first-order perturbation analysis of a simple eigenvalue and the corresponding right and left eigenvectors of a general square matrix, not assumed to be Hermitian or normal.
A. Greenbaum, Ren-Cang Li, M. Overton
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Eigenvalue Expansion of Nonsymmetric Linear Compact Operators in Hilbert Space
Communications in Advanced Mathematical Sciences, 2021 For a symmetric linear compact resp. symmetric densely defined linear operator with compact inverse, expansion theorems in series of eigenvectors are known.
Ludwig Kohaupt
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MASALAH EIGEN DAN EIGENMODE MATRIKS ATAS ALJABAR MIN-PLUS
Barekeng, 2021 Eigen problems and eigenmode are important components related to square matrices. In max-plus algebra, a square matrix can be represented in the form of a graph called a communication graph.
Eka Widia Rahayu +2 more
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Surface Registration with Eigenvalues and Eigenvectors
IEEE Transactions on Visualization and Computer Graphics, 2020 This paper presents a novel surface registration technique using the spectrum of the shapes, which can facilitate accurate localization and visualization of non-isometric deformations of the surfaces.
Hajar Hamidian +3 more
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The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices [PDF]
, 2011 Florent Benaych-Georges +1 more
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Eigenvalues and Jordan Forms of Dual Complex Matrices [PDF]
Communication on Applied Mathematics and Computation, 2023 Dual complex matrices have found applications in brain science. There are two different definitions of the dual complex number multiplication. One is noncommutative. Another is commutative. In this paper, we use the commutative definition.
Liqun Qi, Chunfeng Cui
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Expansions for eigenfunction and eigenvalues of large-$n$ Toeplitz matrices [PDF]
Papers in Physics, 2010 This paper constructs methods for finding convergent expansions for eigenvectors and eigenvalues of large-$n$ Toeplitz matrices based on a situation in which the analogous infinite-$n$ matrix would be singular. It builds upon work done by Dai, Geary, and
Leo P. Kadanoff
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Invariant Subspaces: An Alternative for Introducing Eigenvectors and Eigenvalues
Annales de Didactique et de Sciences Cognitives, 2023 The concepts of eigenvalue and eigenvector are typically approached algorithmically in introductory linear algebra courses. However, a more conceptual orientation involves connecting these notions to the concept of one-dimensional invariant subspace ...
Gisela Camacho, Asuman Oktaç
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Eigenvectors from Eigenvalues Sparse Principal Component Analysis [PDF]
Journal of Computational And Graphical Statistics, 2020 We present a novel technique for sparse principal component analysis. This method, named eigenvectors from eigenvalues sparse principal component analysis (EESPCA), is based on the formula for computing squared eigenvector loadings of a Hermitian matrix ...
H. R. Frost
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Spectral properties for a type of heptadiagonal symmetric matrices
AIMS Mathematics, 2023 In this paper we expressed the eigenvalues of a sort of heptadiagonal symmetric matrices as the zeros of explicit rational functions establishing upper and lower bounds for each of them. From the prescribed eigenvalues, we computed eigenvectors for these
João Lita da Silva
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