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  2. Vector projection - Wikipedia

    en.wikipedia.org/wiki/Vector_projection

    The vector projection (also known as the vector component or vector resolution) of a vector a on (or onto) a nonzero vector b is the orthogonal projection of a onto a straight line parallel to b. The projection of a onto b is often written as proj b ⁡ a {\displaystyle \operatorname {proj} _{\mathbf {b} }\mathbf {a} } or a ∥ b .

  3. Projection - Wikipedia

    en.wikipedia.org/wiki/Projection

    Projection (mathematics), any of several different types of geometrical mappings Projection (linear algebra), a linear transformation P from a vector space to itself such that P 2 = P; Projection (set theory), one of two closely related types of functions or operations in set theory; Projection (measure theory), use of a projection map in ...

  4. Vector (mathematics and physics) - Wikipedia

    en.wikipedia.org/wiki/Vector_(mathematics_and...

    Vector projection, also known as vector resolute or vector component, a linear mapping producing a vector parallel to a second vector; Vector-valued function, a function that has a vector space as a codomain; Vectorization (mathematics), a linear transformation that converts a matrix into a column vector

  5. Projection (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Projection_(linear_algebra)

    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.

  6. Vector notation - Wikipedia

    en.wikipedia.org/wiki/Vector_notation

    The term vector was coined by W. R. Hamilton around 1843, as he revealed quaternions, a system which uses vectors and scalars to span a four-dimensional space. For a quaternion q = a + bi + cj + dk, Hamilton used two projections: S q = a, for the scalar part of q, and V q = bi + cj + dk, the vector part.

  7. Orthogonalization - Wikipedia

    en.wikipedia.org/wiki/Orthogonalization

    In linear algebra, orthogonalization is the process of finding a set of orthogonal vectors that span a particular subspace.Formally, starting with a linearly independent set of vectors {v 1, ... , v k} in an inner product space (most commonly the Euclidean space R n), orthogonalization results in a set of orthogonal vectors {u 1, ... , u k} that generate the same subspace as the vectors v 1 ...

  8. Isometry - Wikipedia

    en.wikipedia.org/wiki/Isometry

    Definition: [7] The midpoint of two elements x and y in a vector space is the vector ⁠ 1 / 2 ⁠ (x + y). Theorem [ 7 ] [ 8 ] — Let A : X → Y be a surjective isometry between normed spaces that maps 0 to 0 ( Stefan Banach called such maps rotations ) where note that A is not assumed to be a linear isometry.

  9. Projectivization - Wikipedia

    en.wikipedia.org/wiki/Projectivization

    In mathematics, projectivization is a procedure which associates with a non-zero vector space V a projective space P(V), whose elements are one-dimensional subspaces of V.More generally, any subset S of V closed under scalar multiplication defines a subset of P(V) formed by the lines contained in S and is called the projectivization of S.