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In the Hilbert space view, this is the orthogonal projection of onto the kernel of the expectation operator, which a continuous linear functional on the Hilbert space (in fact, the inner product with the constant random variable 1), and so this kernel is a closed subspace.
Hilbert projection theorem — For every vector in a Hilbert space and every nonempty closed convex , there exists a unique vector for which ‖ ‖ is equal to := ‖ ‖.. If the closed subset is also a vector subspace of then this minimizer is the unique element in such that is orthogonal to .
A projection on a Hilbert space that is not orthogonal is ... An orthogonal projection is a ... In Riemannian geometry, this is used in the definition of a ...
Hilbert projection theorem – On closed convex subsets in Hilbert space Orthogonal projection – Idempotent linear transformation from a vector space to itself Pages displaying short descriptions of redirect targets
Orthographic projection (also orthogonal projection and analemma) [a] is a means of representing three-dimensional objects in two dimensions.Orthographic projection is a form of parallel projection in which all the projection lines are orthogonal to the projection plane, [2] resulting in every plane of the scene appearing in affine transformation on the viewing surface.
A projection-valued measure π is homogeneous of multiplicity n if and only if the multiplicity function has constant value n. Clearly, Theorem. Any projection-valued measure π taking values in the projections of a separable Hilbert space is an orthogonal direct sum of homogeneous projection-valued measures:
If a normal operator T on a finite-dimensional real [clarification needed] or complex Hilbert space (inner product space) H stabilizes a subspace V, then it also stabilizes its orthogonal complement V ⊥. (This statement is trivial in the case where T is self-adjoint.) Proof. Let P V be the orthogonal projection onto V.
The concept of orthogonality may be extended to a vector space over any field of characteristic not 2 equipped with a quadratic form .Starting from the observation that, when the characteristic of the underlying field is not 2, the associated symmetric bilinear form , = ((+) ()) allows vectors and to be defined as being orthogonal with respect to when (+) () = .