Examples of using Eigenvector in English and their translations into Portuguese
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Colloquial
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Official
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Medicine
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Financial
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Ecclesiastic
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Ecclesiastic
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Computer
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Official/political
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However, the additional requirement that all the entries in the eigenvector be positive implies(by the Perron-Frobenius theorem)
An eigenvalue of the adjacency matrix of a graph is said to be main when it has an eigenvector that is not orthogonal to the vector whose coordinates are equal to1.
real-symmetric matrices have several useful properties: Every generalized eigenvector of a normal matrix is an ordinary eigenvector. .
Since there is one superdiagonal entry, there will be one generalized eigenvector of rank greater than 1 or one could note that the vector space V{\displaystyle V} is of dimension 2, so there can be at most one generalized eigenvector of rank greater than 1.
In linear algebra, a generalized eigenvector of an n× n matrix A{\displaystyle A} is a vector which satisfies certain criteria which are more relaxed than those for an(ordinary) eigenvector.
that is correlated with each eigenvector.
It is shown thatthe principal eigenvector(associated with the largest eigenvalue of formula_72, the adjacency matrix)
it corresponds to an eigenvector of the matrix and, therefore, all its iterates are also eigenvectors, so they all lie on the same line.
HP48 shows the eigenvector matrix in line,
medium networks random showed that the search of the eigenvector centrality of a vertex points to a solution of the medians,
These three diversity metrics were spatially structured by spatial eigenvector mapping which allowed removing the spatial autocorrelation bias,
From a study of the measure of eigenvector centrality, was observed a strong relation between the determination of the vector center with the determination of the output median of an undirected graph, where the centrality of eigenvector ranks the vertexes in order of importance of each one.
The cumulative energy content"g" for the"j"th eigenvector is the sum of the energy content across all of the eigenvalues from 1 through"j":::
associated with this eigenvalue we have a eigenvector with positive entries,
its associated generalized eigenvector v are a pair obeying the relation( A- λ I) k v 0,{\displaystyle\left(A-\lambda I\ right)^{ k}{\ mathbf{v}}=0,} where v is
Eigenvectors of distinct eigenvalues of a normal matrix are orthogonal.
The remaining two complex eigenvectors define the center manifold.
Eigenvectors can be found by exploiting the Cayley-Hamilton theorem.
The eigenvalues and the eigenvectors are complex. Examples.