Search results
Results from the WOW.Com Content Network
Matrix equivalence is an equivalence relation on the space of rectangular matrices. For two rectangular matrices of the same size, their equivalence can also be characterized by the following conditions The matrices can be transformed into one another by a combination of elementary row and column operations.
In the definition of similarity, if the matrix P can be chosen to be a permutation matrix then A and B are permutation-similar; if P can be chosen to be a unitary matrix then A and B are unitarily equivalent. The spectral theorem says that every normal matrix is unitarily equivalent to some diagonal matrix.
Matrix congruence is an equivalence relation. Matrix congruence arises when considering the effect of change of basis on the Gram matrix attached to a bilinear form or quadratic form on a finite-dimensional vector space: two matrices are congruent if and only if they represent the same bilinear form with respect to different bases.
Any matrix can be reduced by elementary row operations to a matrix in reduced row echelon form. Two matrices in reduced row echelon form have the same row space if and only if they are equal. This line of reasoning also proves that every matrix is row equivalent to a unique matrix with reduced row echelon form.
The transpose A T is an invertible matrix. A is row-equivalent to the n-by-n identity matrix I n. A is column-equivalent to the n-by-n identity matrix I n. A has n pivot positions. A has full rank: rank A = n. A has a trivial kernel: ker(A) = {0}. The linear transformation mapping x to Ax is bijective; that is, the equation Ax = b has exactly ...
To see the equivalence, notice that if X is a left R-module then X n is an M n (R)-module where the module structure is given by matrix multiplication on the left of column vectors from X. This allows the definition of a functor from the category of left R -modules to the category of left M n ( R )-modules .
Formally, the construction is as follows. [1] Let be a vector space over a field, and let be a subspace of .We define an equivalence relation on by stating that iff .That is, is related to if and only if one can be obtained from the other by adding an element of .
The equality equivalence relation is the finest equivalence relation on any set, while the universal relation, which relates all pairs of elements, is the coarsest. The relation " ∼ {\displaystyle \sim } is finer than ≈ {\displaystyle \approx } " on the collection of all equivalence relations on a fixed set is itself a partial order ...