Results 1 to 10 of about 197,517 (218)
Eigenvector Sky Subtraction [PDF]
The Astrophysical Journal, 2000 We develop a new method for estimating and removing the spectrum of the sky from deep spectroscopic observations; our method does not rely on simultaneous measurement of the sky spectrum with the object spectrum.
Kurtz, Michael J., Mink, Douglas J.
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The rotation of eigenvectors by a perturbation—II
Journal of Mathematical Analysis and Applications, 1965 Although the behavior of the eigenvalues of a hermitian matrix under perturbation is fairly well understood, there has been almost nothing done on the behavior of the eigenvectors. It is well known that they vary analytically under analytic perturbations but for some purposes one would prefer sharp bounds on the distance between the eigenvectors of a ...
Chandler Davis
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On Differentiating Eigenvalues and Eigenvectors [PDF]
Econometric Theory, 1985 Let X0 be a square matrix (complex or otherwise) and u0 a (normalized) eigenvector associated with an eigenvalue λo of X0, so that the triple (X0, u0, λ0) satisfies the equations Xu = λu, . We investigate the conditions under which unique differentiable functions λ(X) and u(X) exist in a neighborhood of X0 satisfying λ(X0) = λO, u(X0) = u0, Xu = λu ...
Jan R. Magnus
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Eigenvectors in bottleneck algebra
Linear Algebra and its Applications, 1992 The paper deals with a characterization of the eigenvectors in terms of the associated graph and with an alternative way of computing them. Upper and lower bounds for all eigenvectors are given. The approach is illustrated by several numerical examples.
Katarı́na Cechlárová
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Mathematical modeling of the eigenvibrations for the loaded shallow shell [PDF]
E3S Web of Conferences, 2023 The eigenvalue problems modeling of the eigenvibrations of the loaded shallow shell are studied. The asymptotic properties of the eigenvalues and eigenvectors are investigated in dependence on the load parameters.
Samsonov Anton, Solov’ev Sergey
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Journal of Spectral Imaging, 2022 Principal components analysis (PCA), maximum autocorrelation factors (MAF), minimum noise factors (MNF) and maximum difference factors (MDF) models are common factor-based models used for analysis of hyperspectral images.
Neal B. Gallagher
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Electronic Research Archive, 2023 The eigenvalues and eigenvectors of a normalized gaussian operator do not seem to have been previously considered. I solve this problem for 1-dimensional translational systems.
R. F. Snider
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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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A Globally Convergent MCA Algorithm by Generalized Eigen-Decomposition [PDF]
International Journal of Computational Intelligence Systems, 2011 Minor component analysis (MCA) are used in many applications such as curve and surface fitting, robust beam forming, and blind signal separation. Based on the generalized eigen-decomposition, we present a completely different approach that leads to ...
Jianbin Gao, Mao Ye, Jianping Li, Qi Xia
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Applied General Topology, 2022 In this paper, we present some results on fixed point index calculations for multivalued mappings and apply them to prove the existence of solutions to multivalued equations in ordered space, under flexible conditions for the positive eigenvalue.
Vo Viet Tri
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