Module extendr_api::prelude::modules::svd
Expand description
Low level implementation of the SVD of a matrix.
The SVD of a matrix $M$ of shape $(m, n)$ is a decomposition into three components $U$, $S$, and $V$, such that:
- $U$ has shape $(m, m)$ and is a unitary matrix,
- $V$ has shape $(n, n)$ and is a unitary matrix,
- $S$ has shape $(m, n)$ and is zero everywhere except the main diagonal,
- and finally:
$$M = U S V^H.$$
Structs§
- SVD tuning parameters.
Enums§
- Indicates whether the singular vectors are fully computed, partially computed, or skipped.
Functions§
- Computes the singular value decomposition of
matrix
. - See
compute_svd
. - Computes the size and alignment of required workspace for performing a singular value decomposition. $U$ and $V$ may be computed fully, partially, or not computed at all.