- SingularValueDecompositionDC
- SingularValueDecompositionQR
- SingularValueDecompositionQRPivot
- SingularValueDecompositionBisection
- SingularValueDecompositionJacobiHigh
- SingularValueDecompositionJacobiLow
- SingularValueDecompositionBidiagDC
- SingularValueDecompositionBidiagBisect
- SingularValueDecompositionBidiagQR
SingularValueDecompositionBidiagDC
Singular Value Decomposition, divide-and-conquer algorithm for bidiagonal matrices (LAPACK function BDSDC).
Computing for type matrix<double>
bool matrix::SingularValueDecompositionBidiagDC(
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Computing for type matrix<float>
bool matrixf::SingularValueDecompositionBidiagDC(
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Parameters
jobz
[in] ENUM_SVDBIDIAG_Z enumeration value that determines how the singular vectors should be computed.
S
[out] Vector of singular values.
U
[out] Matrix of left singular vectors.
VT
[out] Transposed matrix of right singular vectors.
Return Value
Return true if successful, otherwise false in case of an error.
Note
Computation depends on the values of the jobz and range parameters.
When BLASRANGE_A is set, all singular values are computed, and the lower and upper parameters are ignored.
With the BLASRANGE_V value, only those singular values (and their vectors) that fall within the range of real values specified by the 'lower' and 'upper' parameters are computed.
With the BLASRANGE_I value, only those singular values (and their vectors) that fall within the range of integer indices specified by the 'lower' and 'upper' parameters are computed. For example, with lower=0 and upper=2, only the first three singular values are computed.
A bidiagonal matrix is a square matrix with non-zero main diagonal and one of the sub-diagonals.
Upper bidiagonal matrix
[[x, x, 0, 0, 0],
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Lower bidiagonal matrix
[[x, 0, 0, 0, 0],
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An enumeration defining how left singular vectors should be computed.
ID |
Description |
|---|---|
SVDJOBZ_V |
Compute singular values and singular vectors. |
SVDJOBZ_N |
Compute singular values only. |
See also