org.ujmp.core.doublematrix.calculation.general.decomposition
Interface SVD<T>
public interface SVD<T>
Singular Value Decomposition.
For an m-by-n matrix A, the singular value decomposition is an m-by-(m or n)
orthogonal matrix U, a (m or n)-by-n diagonal matrix S, and an n-by-n
orthogonal matrix V so that A = U*S*V'.
The singular values, sigma[k] = S[k][k], are ordered so that sigma[0] >=
sigma[1] >= ... >= sigma[n-1].
The singular value decompostion always exists, so the constructor will never
fail. The matrix condition number and the effective numerical rank can be
computed from this decomposition.
Method Summary |
T[] |
calc(T source)
|
THRESHOLD
static final int THRESHOLD
- See Also:
- Constant Field Values
MATRIX
static final SVD<Matrix> MATRIX
INSTANCE
static final SVD<Matrix> INSTANCE
UJMP
static final SVD<Matrix> UJMP
MATRIXSMALLSINGLETHREADED
static final SVD<Matrix> MATRIXSMALLSINGLETHREADED
MATRIXLARGESINGLETHREADED
static final SVD<Matrix> MATRIXLARGESINGLETHREADED
MATRIXSMALLMULTITHREADED
static final SVD<Matrix> MATRIXSMALLMULTITHREADED
MATRIXLARGEMULTITHREADED
static final SVD<Matrix> MATRIXLARGEMULTITHREADED
calc
T[] calc(T source)
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