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Toeplitz matrix. In linear algebra, a Toeplitz matrix or diagonal-constant matrix, named after Otto Toeplitz, is a matrix in which each descending diagonal from left to right is constant. For instance, the following matrix is a Toeplitz matrix: Any matrix of the form. is a Toeplitz matrix. If the element of is denoted then we have.
In mathematics, particularly in matrix theory, a permutation matrix is a square binary matrix that has exactly one entry of 1 in each row and each column with all other entries 0. [ 1]: 26 An n × n permutation matrix can represent a permutation of n elements. Pre- multiplying an n -row matrix M by a permutation matrix P, forming PM, results in ...
In numerical analysis and linear algebra, lower–upper ( LU) decomposition or factorization factors a matrix as the product of a lower triangular matrix and an upper triangular matrix (see matrix decomposition ). The product sometimes includes a permutation matrix as well. LU decomposition can be viewed as the matrix form of Gaussian elimination.
Rotation matrix. In linear algebra, a rotation matrix is a transformation matrix that is used to perform a rotation in Euclidean space. For example, using the convention below, the matrix. rotates points in the xy plane counterclockwise through an angle θ about the origin of a two-dimensional Cartesian coordinate system.
In mathematics, particularly in linear algebra, matrix multiplication is a binary operation that produces a matrix from two matrices. For matrix multiplication, the number of columns in the first matrix must be equal to the number of rows in the second matrix. The resulting matrix, known as the matrix product, has the number of rows of the ...
Tridiagonal matrix algorithm. In numerical linear algebra, the tridiagonal matrix algorithm, also known as the Thomas algorithm (named after Llewellyn Thomas ), is a simplified form of Gaussian elimination that can be used to solve tridiagonal systems of equations. A tridiagonal system for n unknowns may be written as. where and .
In MATLAB, the Hadamard product is expressed as "dot multiply": a .* b, or the function call: times(a, b). [18] It also has analogous dot operators which include, for example, the operators a .^ b and a ./ b. [19] Because of this mechanism, it is possible to reserve * and ^ for matrix multiplication and matrix exponentials, respectively.
Any circulant is a matrix polynomial (namely, the associated polynomial) in the cyclic permutation matrix : − − where is given by the companion matrix. The set of × circulant matrices forms an - dimensional vector space with respect to addition and scalar multiplication. This space can be interpreted as the space of functions on the cyclic ...