org.jblas
Class Singular

java.lang.Object
  extended by 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.


© 2008-2010 by Mikio L. Braun and contributors