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  2. Matrix representation of Maxwell's equations - Wikipedia

    en.wikipedia.org/wiki/Matrix_representation_of...

    One of the early uses of the matrix forms of the Maxwell's equations was to study certain symmetries, and the similarities with the Dirac equation. The matrix form of the Maxwell's equations is used as a candidate for the Photon Wavefunction. [8] Historically, the geometrical optics is based on the Fermat's principle of least time. Geometrical ...

  3. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    B i consists of n block matrices of size m × m, stacked column-wise, and all these matrices are all-zero except for the i-th one, which is a m × m identity matrix I m. Then the vectorized version of X can be expressed as follows: vec ⁡ ( X ) = ∑ i = 1 n B i X e i {\displaystyle \operatorname {vec} (\mathbf {X} )=\sum _{i=1}^{n}\mathbf {B ...

  4. Matrix (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Matrix_(mathematics)

    Multiplication of two matrices is defined if and only if the number of columns of the left matrix is the same as the number of rows of the right matrix. If A is an m×n matrix and B is an n×p matrix, then their matrix product AB is the m×p matrix whose entries are given by dot product of the corresponding row of A and the corresponding column ...

  5. Multilinear map - Wikipedia

    en.wikipedia.org/wiki/Multilinear_map

    One can consider multilinear functions, on an n×n matrix over a commutative ring K with identity, as a function of the rows (or equivalently the columns) of the matrix. Let A be such a matrix and a i, 1 ≤ i ≤ n, be the rows of A. Then the multilinear function D can be written as = (, …,),

  6. Matrix analysis - Wikipedia

    en.wikipedia.org/wiki/Matrix_analysis

    In mathematics, particularly in linear algebra and applications, matrix analysis is the study of matrices and their algebraic properties. [1] Some particular topics out of many include; operations defined on matrices (such as matrix addition, matrix multiplication and operations derived from these), functions of matrices (such as matrix exponentiation and matrix logarithm, and even sines and ...

  7. Distance matrix - Wikipedia

    en.wikipedia.org/wiki/Distance_matrix

    That is, if M = (x ij) with 1 ≤ i, j ≤ N is a distance matrix for a metric distance, then the entries on the main diagonal are all zero (that is, the matrix is a hollow matrix), i.e. x ii = 0 for all 1 ≤ i ≤ N, all the off-diagonal entries are positive (x ij > 0 if i ≠ j), (that is, a non-negative matrix), the matrix is a symmetric ...

  8. Shear mapping - Wikipedia

    en.wikipedia.org/wiki/Shear_mapping

    Thus every shear matrix has an inverse, and the inverse is simply a shear matrix with the shear element negated, representing a shear transformation in the opposite direction. In fact, this is part of an easily derived more general result: if S is a shear matrix with shear element λ, then S n is a shear matrix whose shear element is simply nλ.

  9. Euclidean distance matrix - Wikipedia

    en.wikipedia.org/wiki/Euclidean_distance_matrix

    In mathematics, a Euclidean distance matrix is an n×n matrix representing the spacing of a set of n points in Euclidean space. For points x 1 , x 2 , … , x n {\displaystyle x_{1},x_{2},\ldots ,x_{n}} in k -dimensional space ℝ k , the elements of their Euclidean distance matrix A are given by squares of distances between them.