Search results
Results From The WOW.Com Content Network
The th column of an identity matrix is the unit vector, a vector whose th entry is 1 and 0 elsewhere. The determinant of the identity matrix is 1, and its trace is . The identity matrix is the only idempotent matrix with non-zero determinant. That is, it is the only matrix such that:
Every finite-dimensional matrix has a rank decomposition: Let be an matrix whose column rank is . Therefore, there are r {\textstyle r} linearly independent columns in A {\textstyle A} ; equivalently, the dimension of the column space of A {\textstyle A} is r {\textstyle r} .
A common case is finding the inverse of a low-rank update A + UCV of A (where U only has a few columns and V only a few rows), or finding an approximation of the inverse of the matrix A + B where the matrix B can be approximated by a low-rank matrix UCV, for example using the singular value decomposition.
In mathematics, the general linear group of degree n is the set of n×n invertible matrices, together with the operation of ordinary matrix multiplication.This forms a group, because the product of two invertible matrices is again invertible, and the inverse of an invertible matrix is invertible, with the identity matrix as the identity element of the group.
In numerical analysis, interpolative decomposition (ID) factors a matrix as the product of two matrices, one of which contains selected columns from the original matrix, and the other of which has a subset of columns consisting of the identity matrix and all its values are no greater than 2 in absolute value.
Given a square invertible matrix , an matrix , and a matrix , let be an matrix such that = +. Then, assuming ( I k + V A − 1 U ) {\displaystyle \left(I_{k}+VA^{-1}U\right)} is invertible, we have B − 1 = A − 1 − A − 1 U ( I k + V A − 1 U ) − 1 V A − 1 . {\displaystyle B^{-1}=A^{-1}-A^{-1}U\left(I_{k}+VA^{-1}U\right)^{-1}VA^{-1}.}
Likewise, the Gram matrix of the rows or columns of a unitary matrix is the identity matrix. The rank of the Gram matrix of vectors in R k {\displaystyle \mathbb {R} ^{k}} or C k {\displaystyle \mathbb {C} ^{k}} equals the dimension of the space spanned by these vectors.
The map is a chart in which countries are positioned based on their scores for the two values mapped on the x-axis (survival values versus self-expression values) and the y-axis (traditional values versus secular-rational values). [2] The map shows where societies are located in these two dimensions.