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eigenvector (Definition)

Let $ A$ be an $ n \times n$ square matrix and $ x$ an $ n\times 1$ column vector. Then a (right) eigenvector of $ A$ is a nonzero vector $ x$ such that

$\displaystyle Ax = \lambda x $

for some scalar $ \lambda$, i.e. such that the image of $ x$ under the transformation $ A$ is a scalar multiple of $ x$. One can similarly define left eigenvectors in the case that $ A$ acts on the right.

One can find eigenvectors by first finding eigenvalues, then for each eigenvalue $ \lambda_i$, solving the system

$\displaystyle (A-\lambda_i I) x_i = 0 $

to find a form which characterizes the eigenvector $ x_i$ (any multiple of $ x_i$ is also an eigenvector). Of course, this is not necessarily the best way to do it; for this, see singular value decomposition.



"eigenvector" is owned by mathcam. [ full author list (2) | owner history (1) ]
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See Also: singular value decomposition, eigenvalue, eigenvalue problem, similar matrix, diagonalization

Also defines:  scalar multiple

Attachments:
generalized eigenvector (Definition) by CWoo
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Cross-references: singular value decomposition, eigenvalue, finding eigenvalues, acts on, eigenvectors, transformation, image, scalar, vector, right, column vector, square matrix
There are 24 references to this entry.

This is version 8 of eigenvector, born on 2002-01-19, modified 2007-05-12.
Object id is 1497, canonical name is Eigenvector.
Accessed 37881 times total.

Classification:
AMS MSC15-00 (Linear and multilinear algebra; matrix theory :: General reference works )
 15A18 (Linear and multilinear algebra; matrix theory :: Eigenvalues, singular values, and eigenvectors)
 65-00 (Numerical analysis :: General reference works )
 65F15 (Numerical analysis :: Numerical linear algebra :: Eigenvalues, eigenvectors)

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