Linear and multilinear algebra; matrix theory Concept
Eigenvector
Summary
An eigenvector of a linear map from a space to itself is a nonzero vector that the map sends to a scalar multiple of itself.
Where this leads
24 pages build on this one.
- Power iteration
- Hilbert–Schmidt expansion theorem
- Eigenfunction of an integral operator
- Bilinear series of a symmetric kernel
- Perron–Frobenius theorem
- Inverse iteration
- Spectral theorem for compact self-adjoint operators
- Courant–Fischer characterization of characteristic values
- Parry measure
- Divide-and-conquer eigenvalue algorithm
- Eigendecomposition
- Lidskii's trace formula for integral operators
- Spectrum of the Laplace–Beltrami operator
- Jentzsch's theorem on positive kernels
- Mercer's theorem
- Principal component analysis
- Multidimensional scaling
- Eigenvalue algorithm
- Spectral theory
- Singular values of a compact operator
- Krein–Rutman theorem
- Schmidt's singular value decomposition of a kernel
- Rayleigh quotient iteration
- Eigenvalue perturbation
Further reading
- Web https://en.wikipedia.org/wiki/Eigenvalues_and_eigenvectors, General definition
About this page
| Tag | 0N6960W0BV |
|---|---|
| URI | m2://0N6960W0BV |
| Kind | concept |
| Writing | W0 stub |
| MSC | 15A18 |
| Specializes | Generalised eigenvector |
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What links here
Definitions
Used by
- Power iteration
- Eigenfunction of an integral operator
- Perron–Frobenius theorem
- Inverse iteration
- Spectral theorem for compact self-adjoint operators
- Divide-and-conquer eigenvalue algorithm
- Eigendecomposition
- Principal component analysis
- Multidimensional scaling
- Eigenvalue algorithm
- Spectral theory
- Krein–Rutman theorem
- Rayleigh quotient iteration
- Eigenvalue perturbation