In linear algebra and functional analysis, a projection is a linear transformation from a vector space to itself (an endomorphism) such that . That is, whenever is applied twice to any vector, it gives the same result as if it were applied once (i.e. is idempotent). It leaves its unchanged. This definition of "projection" formalizes and generalizes the idea of graphical projection. One can also consider the effect of a projection on a geometrical object by examining the effect of the projection on points in the object. A projection on a vector space is a linear operator such that . When has an inner product and is complete (i.e. when is a Hilbert space) the concept of orthogonality can be used. A projection on a Hilbert space is called an orthogonal projection if it satisfies for all . A projection on a Hilbert space that is not orthogonal is called an oblique projection. A square matrix is called a projection matrix if it is equal to its square, i.e. if . A square matrix is called an orthogonal projection matrix if for a real matrix, and respectively for a complex matrix, where denotes the transpose of and denotes the adjoint or Hermitian transpose of . A projection matrix that is not an orthogonal projection matrix is called an oblique projection matrix. The eigenvalues of a projection matrix must be 0 or 1. For example, the function which maps the point in three-dimensional space to the point is an orthogonal projection onto the xy-plane. This function is represented by the matrix The action of this matrix on an arbitrary vector is To see that is indeed a projection, i.e., , we compute Observing that shows that the projection is an orthogonal projection. A simple example of a non-orthogonal (oblique) projection is Via matrix multiplication, one sees that showing that is indeed a projection. The projection is orthogonal if and only if because only then By definition, a projection is idempotent (i.e. ). Every projection is an open map, meaning that it maps each open set in the domain to an open set in the subspace topology of the .

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related publications (70)
Related concepts (21)
Hilbert space
In mathematics, Hilbert spaces (named after David Hilbert) allow the methods of linear algebra and calculus to be generalized from (finite-dimensional) Euclidean vector spaces to spaces that may be infinite-dimensional. Hilbert spaces arise naturally and frequently in mathematics and physics, typically as function spaces. Formally, a Hilbert space is a vector space equipped with an inner product that induces a distance function for which the space is a complete metric space.
Eigenvalue algorithm
In numerical analysis, one of the most important problems is designing efficient and stable algorithms for finding the eigenvalues of a matrix. These eigenvalue algorithms may also find eigenvectors. Eigenvalues and eigenvectors and Generalized eigenvector Given an n × n square matrix A of real or complex numbers, an eigenvalue λ and its associated generalized eigenvector v are a pair obeying the relation where v is a nonzero n × 1 column vector, I is the n × n identity matrix, k is a positive integer, and both λ and v are allowed to be complex even when A is real.
Outer product
In linear algebra, the outer product of two coordinate vectors is the matrix whose entries are all products of an element in the first vector with an element in the second vector. If the two coordinate vectors have dimensions n and m, then their outer product is an n × m matrix. More generally, given two tensors (multidimensional arrays of numbers), their outer product is a tensor. The outer product of tensors is also referred to as their tensor product, and can be used to define the tensor algebra.
Show more

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.