- SingularValueDecompositionDC
- SingularValueDecompositionQR
- SingularValueDecompositionQRPivot
- SingularValueDecompositionBisect
- SingularValueDecompositionJacobiHigh
- SingularValueDecompositionJacobiLow
- SingularValueDecompositionBidiagDC
- SingularValueDecompositionBidiagBisect
SingularValueDecompositionQR
Singular Value Decomposition, QR algorithm. Considered a classical SVD algorithm (lapack function GESVD).
Computing for type matrix<double>
bool matrix::SingularValueDecompositionQR(
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Computing for type matrix<float>
bool matrix::SingularValueDecompositionQR(
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Computing for type matrix<complex>
bool matrix::SingularValueDecompositionQR(
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Parameters
jobu
[in] ENUM_SVD_Z enumeration value defining how the left singular vectors should be computed.
jobv
[in] ENUM_SVD_Z enumeration value defining how the right singular vectors should be computed.
S
[out] Vector of singular values.
U
[out] Matrix of left singular vectors.
VT
[out] Matrix of right singular vectors.
Return Value
Return true if successful, otherwise false in case of an error.
Note
Computation depends on the value of the jobu and jobv parameters.
When set to SVDZ_N, the left (jobu) and right (jobv) vectors are not computed. Singular values are always computed.
When set to SVDZ_A, the full matrices of vectors U (jobu) or VT (jobv) are computed.
With the value SVDZ_S, truncated matrices of vectors U (jobu) or VT (jobv) are computed.
ENUM_SVD_Z
An enumeration defining the way to compute left and right singular vectors.
ID |
Description |
---|---|
SVDZ_N |
Columns U or rows VT are not computed |
SVDZ_A |
All M columns of U or all N columns of VT are returned in arrays U and VT |
SVDZ_S |
The first min(M,N) columns of U or the first min(M,N) columns of VT are returned in arrays U and VT |
See also
SingularValueDecompositionDC, SingularValueDecompositionQRPivot