Noun
(linear algebra) given a linear transformation
A
{\displaystyle A}
, a vector
x
{\displaystyle x}
such that
A
x
=
λ
x
{\displaystyle Ax=\lambda x}
for some scalar
λ
{\displaystyle \lambda }
(linear algebra) specifically, given a matrix A, the eigenvector of the transformation "left-side multiplication by A"
Source: en.wiktionary.orgAssuming that the matrix W is a primitive matrix ( irreducible and aperiodic ), then after very many generations only the eigenvector with the largest eigenvalue will prevail, and it is this quasispecies that will eventually dominate. Source: Internet
Each eigenstate of an observable corresponds to an eigenvector of the operator, and the associated eigenvalue corresponds to the value of the observable in that eigenstate. Source: Internet
Moreover, the eigenvectors are not unique because any linear combination of eigenvectors for the same eigenvalue is also an eigenvector for that eigenvalue. Source: Internet
The components of this eigenvector give the relative abundance of each sequence at equilibrium. Source: Internet
The weights can be computed from the corresponding eigenvectors: If is a normalized eigenvector (i. Source: Internet