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Matrix decomposition

In the mathematical discipline of linear algebra, a matrix decomposition is a factorization of a matrix into some canonical form. There are several different decompositions of a given matrix and the decomposition used depends on the problem we want to solve. In numerical analysis for example different decompositions are used to implement efficient matrix algorithms.

Example

When solving a system of linear equations the matrix A can be decomposed via the LU decomposition. The LU decomposition factorizes a matrix into a lower triangular matrix L and an upper triangular matrix U. The matrices L and U are much easier to solve than the original matrix A.

See also

Topics in mathematics related to linear algebra

Vectors | Vector spaces | Linear span | Linear transformation | Linear independence | Linear combination | Basis | Column space | Row space | Dual space | Orthogonality | Eigenvector | Eigenvalue | Least squares regressions | Outer product | Cross product | Dot product | Transpose | Matrix decomposition

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