- Extreme Optimization
- Documentation
- Vector and Matrix Library User's Guide
- Matrix Decompositions
- The LU Decomposition
- The QR Decomposition
- The Cholesky Decomposition
- The Symmetric Indefinite Decomposition
- The Eigenvalue Decomposition
- The Generalized Eigenvalue Decomposition
- The Singular Value Decomposition
- The Generalized Singular Value Decomposition
- Non-Negative Matrix Factorization
- Solving Linear Systems

Matrix Decompositions | Extreme Optimization Numerical Libraries for .NET Professional |

A matrix decomposition or factorization is a representation of a matrix as a product of two or more matrices. Decomposing a matrix is often the first step in the solution of a problem in linear algebra. The matrices in the decomposition usually have some special properties, which can be used to simplify the solution. A decomposition is often called a factorization. The two words are synonyms.

The **Extreme Optimization Numerical Libraries for .NET** contains a series of classes that implement a
number of standard decompositions. These classes are contained in the Extreme.Mathematics.LinearAlgebra namespace.

In this section:

- The LU Decomposition
- The QR Decomposition
- The Cholesky Decomposition
- The Symmetric Indefinite Decomposition
- The Eigenvalue Decomposition
- The Generalized Eigenvalue Decomposition
- The Singular Value Decomposition
- The Generalized Singular Value Decomposition
- Non-Negative Matrix Factorization
- Solving Linear Systems

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