org.jblas
Class Singular

java.lang.Object
  org.jblas.Singular

public class Singular
extends java.lang.Object

Constructor Summary

Singular()

Method Summary

static DoubleMatrix[]	fullSVD(DoubleMatrix A) Compute a singular-value decomposition of A.
static FloatMatrix[]	fullSVD(FloatMatrix A) Compute a singular-value decomposition of A.
static ComplexDoubleMatrix[]	sparseSVD(ComplexDoubleMatrix A)
static ComplexFloatMatrix[]	sparseSVD(ComplexFloatMatrix A)
static DoubleMatrix[]	sparseSVD(DoubleMatrix A) Compute a singular-value decomposition of A (sparse variant).
static FloatMatrix[]	sparseSVD(FloatMatrix A) Compute a singular-value decomposition of A (sparse variant).
static DoubleMatrix	SVDValues(ComplexDoubleMatrix A) Compute the singular values of a complex matrix.
static FloatMatrix	SVDValues(ComplexFloatMatrix A) Compute the singular values of a complex matrix.
static DoubleMatrix	SVDValues(DoubleMatrix A) Compute the singular values of a matrix.
static FloatMatrix	SVDValues(FloatMatrix A) Compute the singular values of a matrix.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Singular

public Singular()

Method Detail

fullSVD

public static DoubleMatrix[] fullSVD(DoubleMatrix A)

Compute a singular-value decomposition of A.

Returns:

A DoubleMatrix[3] array of U, S, V such that A = U * diag(S) * V'

sparseSVD

public static DoubleMatrix[] sparseSVD(DoubleMatrix A)

Compute a singular-value decomposition of A (sparse variant). Sparse means that the matrices U and V are not square but only have as many columns (or rows) as possible.

Parameters:

A -

Returns:

A DoubleMatrix[3] array of U, S, V such that A = U * diag(S) * V'

sparseSVD

public static ComplexDoubleMatrix[] sparseSVD(ComplexDoubleMatrix A)

SVDValues

public static DoubleMatrix SVDValues(DoubleMatrix A)

Compute the singular values of a matrix.

Parameters:

A - DoubleMatrix of dimension m * n

Returns:

A min(m, n) vector of singular values.

SVDValues

public static DoubleMatrix SVDValues(ComplexDoubleMatrix A)

Compute the singular values of a complex matrix.

Parameters:

A - ComplexDoubleMatrix of dimension m * n

Returns:

A real-valued (!) min(m, n) vector of singular values.

fullSVD

public static FloatMatrix[] fullSVD(FloatMatrix A)

Compute a singular-value decomposition of A.

Returns:

A FloatMatrix[3] array of U, S, V such that A = U * diag(S) * V'

sparseSVD

public static FloatMatrix[] sparseSVD(FloatMatrix A)

Compute a singular-value decomposition of A (sparse variant). Sparse means that the matrices U and V are not square but only have as many columns (or rows) as possible.

Parameters:

A -

Returns:

A FloatMatrix[3] array of U, S, V such that A = U * diag(S) * V'

sparseSVD

public static ComplexFloatMatrix[] sparseSVD(ComplexFloatMatrix A)

SVDValues

public static FloatMatrix SVDValues(FloatMatrix A)

Compute the singular values of a matrix.

Parameters:

A - FloatMatrix of dimension m * n

Returns:

A min(m, n) vector of singular values.

SVDValues

public static FloatMatrix SVDValues(ComplexFloatMatrix A)

Compute the singular values of a complex matrix.

Parameters:

A - ComplexFloatMatrix of dimension m * n

Returns:

A real-valued (!) min(m, n) vector of singular values.