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For a symmetric matrix A, the vector vec(A) contains more information than is strictly necessary, since the matrix is completely determined by the symmetry together with the lower triangular portion, that is, the n(n + 1)/2 entries on and below the main diagonal.
Matrices can be used to compactly write and work with multiple linear equations, that is, systems of linear equations. For example, if A is an m×n matrix, x designates a column vector (that is, n×1-matrix) of n variables x 1, x 2, ..., x n, and b is an m×1-column vector, then the matrix equation =
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 = (, …,),
With respect to an n-dimensional matrix, an n+1-dimensional matrix can be described as an augmented matrix. In the physical sciences , an active transformation is one which actually changes the physical position of a system , and makes sense even in the absence of a coordinate system whereas a passive transformation is a change in the ...
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 ...
In mathematics, a block matrix or a partitioned matrix is a matrix that is interpreted as having been broken into sections called blocks or submatrices. [1] [2]Intuitively, a matrix interpreted as a block matrix can be visualized as the original matrix with a collection of horizontal and vertical lines, which break it up, or partition it, into a collection of smaller matrices.
This reduces the number of matrix additions and subtractions from 18 to 15. The number of matrix multiplications is still 7, and the asymptotic complexity is the same. [6] The algorithm was further optimised in 2017, [7] reducing the number of matrix additions per step to 12 while maintaining the number of matrix multiplications, and again in ...
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 ...