From Wakapon
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Singular Value Decomposition (SVD) is the process of decomposing a matrix A this way: | Singular Value Decomposition (SVD) is the process of decomposing a matrix A this way: | ||
| − | <math>\ | + | <math>\left [ \bold{A} \right ] = \left [ \bold{U} \right ] \cdot \left [ \bold{\Sigma} \right ] \cdot \left [ \bold{V} \right ]^T</math> |
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| + | [[File:SVD.png]] | ||
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=== LU Decomposition === | === LU Decomposition === | ||
Revision as of 16:34, 30 July 2017
Contents
Matrix Decomposition Methods
QR Decomposition
SVD Decomposition
Singular Value Decomposition (SVD) is the process of decomposing a matrix A this way:
<math>\left [ \bold{A} \right ] = \left [ \bold{U} \right ] \cdot \left [ \bold{\Sigma} \right ] \cdot \left [ \bold{V} \right ]^T</math>
