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>\Biggl | + | <math>\Biggl\[ A \Biggr]</math> |
| + | |||
| + | = \Biggl\[ U \Biggr] \dot \Biggl\[ \Sigma \Biggr] \dot \Biggl\[ V \Biggr]^T</math> | ||
=== LU Decomposition === | === LU Decomposition === | ||
Revision as of 16:26, 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>\Biggl\[ A \Biggr]</math>
= \Biggl\[ U \Biggr] \dot \Biggl\[ \Sigma \Biggr] \dot \Biggl\[ V \Biggr]^T</math>