When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Row and column vectors - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_vectors

    The matrix product of a column and a row vector gives the outer product of two vectors a, b, an example of the more general tensor product. The matrix product of the column vector representation of a and the row vector representation of b gives the components of their dyadic product,

  3. 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).

  4. Bra–ket notation - Wikipedia

    en.wikipedia.org/wiki/Bra–ket_notation

    In the simple case where we consider the vector space , a ket can be identified with a column vector, and a bra as a row vector. If, moreover, we use the standard Hermitian inner product on C n {\displaystyle \mathbb {C} ^{n}} , the bra corresponding to a ket, in particular a bra m | and a ket | m with the same label are conjugate transpose .

  5. 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.

  6. Inner product space - Wikipedia

    en.wikipedia.org/wiki/Inner_product_space

    Inner product spaces generalize Euclidean vector spaces, in which the inner product is the dot product or scalar product of Cartesian coordinates. Inner product spaces of infinite dimension are widely used in functional analysis. Inner product spaces over the field of complex numbers are sometimes referred to as unitary spaces.

  7. Matrix multiplication - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication

    A coordinate vector is commonly organized as a column matrix (also called a column vector), which is a matrix with only one column. So, a column vector represents both a coordinate vector, and a vector of the original vector space. A linear map A from a vector space of dimension n into a vector space of dimension m maps a column vector

  8. Transpose - Wikipedia

    en.wikipedia.org/wiki/Transpose

    Furthermore, these products are symmetric matrices. Indeed, the matrix product A A T has entries that are the inner product of a row of A with a column of A T. But the columns of A T are the rows of A, so the entry corresponds to the inner product of two rows of A. If p i j is the entry of the product, it is obtained from rows i and j in A.

  9. Vector notation - Wikipedia

    en.wikipedia.org/wiki/Vector_notation

    A vector specified as a row matrix is known as a row vector; ... In addition to the standard inner product notation, the dot product notation (using the dot as an ...