In the mathematical discipline of linear algebra, a matrix decomposition is a factorization of a matrix into a product of matrices. There are many different matrix decompositions; each finds use among a particular class of problems.
Decompositions related to solving systems of linear equations
- LU decomposition
- LU reduction
- Block LU decomposition
- Rank factorization
- Cholesky decomposition
- QR decomposition
- RRQR factorization
- Singular value decomposition
Decompositions based on eigenvalues and related concepts
- Eigendecomposition
- Jordan decomposition
- Schur decomposition
- QZ decomposition
- Takagi's factorization