Linear and multilinear algebra; matrix theory Inner product spaces Concept
Orthogonal projection
Summary
The orthogonal projection onto a subspace sends each vector to the unique vector of whose difference with it is orthogonal to .
Where this leads
21 pages build on this one.
- Ergodic decomposition
- Wold's decomposition theorem
- Commutant lifting theorem
- Ordinary least squares
- Frisch–Waugh–Lovell theorem
- Kingman's subadditive ergodic theorem
- Schwarz alternating method
- Von Neumann bicommutant theorem
- Kaczmarz method
- Birkhoff's ergodic theorem
- Instrumental variables estimation
- Oseledets theorem
- Least squares approximation
- Bergman projection
- von Neumann mean ergodic theorem
- Murray–von Neumann classification of factors
- Projection-valued measure
- Partial autocorrelation function
- Pesin theory
- Additive Schwarz method
- Sz.-Nagy's dilation theorem
Further reading
- Web https://en.wikipedia.org/wiki/Projection_(linear_algebra), Orthogonal projections
About this page
| Tag | 0B8KZRT28M |
|---|---|
| URI | m2://0B8KZRT28M |
| Kind | concept |
| Writing | W0 stub |
| MSC | 15A04, 46C05 |
| Specializes | Projection |
Markdown · JSON · Edit on GitHub
What this page needs for W1
- an inventory row: the row of the inventory that the node accounts for (0 of 1)
The writing levels say how complete the text of a page is. They do not measure its truth.
What links here
Definitions
Used by
- Wold's decomposition theorem
- Commutant lifting theorem
- Ordinary least squares
- Frisch–Waugh–Lovell theorem
- Schwarz alternating method
- Von Neumann bicommutant theorem
- Kaczmarz method
- Instrumental variables estimation
- Least squares approximation
- Bergman projection
- von Neumann mean ergodic theorem
- Murray–von Neumann classification of factors
- Projection-valued measure
- Partial autocorrelation function
- Additive Schwarz method
- Sz.-Nagy's dilation theorem