When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Euclidean vector - Wikipedia

    en.wikipedia.org/wiki/Euclidean_vector

    A Euclidean vector may possess a definite initial point and terminal point; such a condition may be emphasized calling the result a bound vector. [12] When only the magnitude and direction of the vector matter, and the particular initial or terminal points are of no importance, the vector is called a free vector .

  3. Euclidean space - Wikipedia

    en.wikipedia.org/wiki/Euclidean_space

    A Euclidean vector space is a finite-dimensional inner product space over the real numbers. [6] A Euclidean space is an affine space over the reals such that the associated vector space is a Euclidean vector space. Euclidean spaces are sometimes called Euclidean affine spaces to distinguish them from Euclidean vector spaces. [6]

  4. Dot product - Wikipedia

    en.wikipedia.org/wiki/Dot_product

    The self dot product of a complex vector =, involving the conjugate transpose of a row vector, is also known as the norm squared, = ‖ ‖, after the Euclidean norm; it is a vector generalization of the absolute square of a complex scalar (see also: Squared Euclidean distance).

  5. Vector (mathematics and physics) - Wikipedia

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

    In the natural sciences, a vector quantity (also known as a vector physical quantity, physical vector, or simply vector) is a vector-valued physical quantity. [9] [10] It is typically formulated as the product of a unit of measurement and a vector numerical value (), often a Euclidean vector with magnitude and direction.

  6. Outer product - Wikipedia

    en.wikipedia.org/wiki/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.

  7. Standard basis - Wikipedia

    en.wikipedia.org/wiki/Standard_basis

    Every vector a in three dimensions is a linear combination of the standard basis vectors i, j and k.. In mathematics, the standard basis (also called natural basis or canonical basis) of a coordinate vector space (such as or ) is the set of vectors, each of whose components are all zero, except one that equals 1. [1]

  8. Projective plane - Wikipedia

    en.wikipedia.org/wiki/Projective_plane

    Let K 3 denote the set of all triples x = (x 0, x 1, x 2) of elements of K (a Cartesian product viewed as a vector space). For any nonzero x in K 3, the minimal subspace of K 3 containing x (which may be visualized as all the vectors in a line through the origin) is the subset {:} of K 3.

  9. Dyadics - Wikipedia

    en.wikipedia.org/wiki/Dyadics

    When V is Euclidean n-space, we can use the inner product to identify the dual space with V itself, making a dyadic tensor an elementary tensor product of two vectors in Euclidean space. In this sense, the unit dyadic ij is the function from 3-space to itself sending a 1 i + a 2 j + a 3 k to a 2 i, and jj sends this sum to a 2 j.