Results 11 to 20 of about 197,517 (218)
A Note on Eigenvalues and Asymmetric Graphs
Axioms, 2023 This note is intended as a contribution to the study of quantitative measures of graph complexity that use entropy measures based on symmetry. Determining orbit sizes of graph automorphism groups is a key part of such studies. Here we focus on an extreme
Abdullah Lotfi +2 more
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Energies, 2023 Distributed energy resource (DER) has become an effective attempt in promoting use of renewable energy resources for electricity generation. The core intention of this study is to expand an approach for optimally placing several DER units to attain the ...
Ardiaty Arief, Muhammad Bachtiar Nappu
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Size of nodal domains of the eigenvectors of a G(n,p) graph [PDF]
, 2020 Consider an eigenvector of the adjacency matrix of a G(n, p) graph. A nodal domain is a connected component of the set of vertices where this eigenvector has a constant sign. It is known that with high probability, there are exactly two nodal domains for
Bloemendal A., Stroock D.W., Zelditch S.
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The American Mathematical Monthly, 2022 The recursively-constructed family of Mandelbrot matrices $M_n$ for $n=1$, $2$, $\ldots$ have nonnegative entries (indeed just $0$ and $1$, so each $M_n$ can be called a binary matrix) and have eigenvalues whose negatives $-λ= c$ give periodic orbits under the Mandelbrot iteration, namely $z_k = z_{k-1}^2+c$ with $z_0=0$, and are thus contained in the ...
Neil J. Calkin +4 more
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Energies, 2021 Power systems may encounter disturbances during operation as a result of switching of various components, etc. Such perturbations include transformer tap-changing action, load variations, and line outages due to various types of faults of which an earth ...
Ewaoche John Okampo +2 more
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Convergence of Eigenvector Continuation [PDF]
Physical Review Letters, 2021 Eigenvector continuation is a computational method that finds the extremal eigenvalues and eigenvectors of a Hamiltonian matrix with one or more control parameters. It does this by projection onto a subspace of eigenvectors corresponding to selected training values of the control parameters.
Avik Sarkar, Dean Lee
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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 of Permutation Matrices [PDF]
Advances in Pure Mathematics, 2015 The spectral properties of special matrices have been widely studied, because of their applications. We focus on permutation matrices over a finite field and, more concretely, we compute the minimal annihilating polynomial, and a set of linearly independent eigenvectors from the decomposition in disjoint cycles of the permutation ...
García Planas, María Isabel +1 more
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[OII] Emission, Eigenvector 1 and Orientation in Radio-quiet Quasars [PDF]
, 2000 We present supportive evidence that the Boroson and Green eigenvector 1 is not driven by source orientation. Until recently it was generally accepted that eigenvector 1 does not depend on orientation as it strongly correlates with [OIII]5007 emission ...
Antonucci R. +14 more
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Some Properties of SINR Regions for Standard Interference Mappings
SICE Journal of Control, Measurement, and System Integration, 2020 In 1995, Yates proposed an axiomatic framework of standard interference mappings and examined the iterative power control algorithm for a system with interference constraints.
Susumu Shindoh
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