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.


Nested Class Summary
static class SVD.SVDMatrix
           
 
Field Summary
static SVD<Matrix> INSTANCE
           
static SVD<Matrix> MATRIX
           
static SVD<Matrix> MATRIXLARGEMULTITHREADED
           
static SVD<Matrix> MATRIXLARGESINGLETHREADED
           
static SVD<Matrix> MATRIXSMALLMULTITHREADED
           
static SVD<Matrix> MATRIXSMALLSINGLETHREADED
           
static int THRESHOLD
           
static SVD<Matrix> UJMP
           
 
Method Summary
 T[] calc(T source)
           
 

Field Detail

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
Method Detail

calc

T[] calc(T source)


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