mikera.matrixx.decompose.impl.svd

Class SvdImplicitQr

java.lang.Object

mikera.matrixx.decompose.impl.svd.SvdImplicitQr

public class SvdImplicitQr
extends Object

Computes the Singular value decomposition of a matrix using the implicit QR algorithm for singular value decomposition. It works by first by transforming the matrix to a bidiagonal A=U*B*V^T form, then it implicitly computing the eigenvalues of the B^TB matrix, which are the same as the singular values in the original A matrix.

Based off of the description provided in:

David S. Watkins, "Fundamentals of Matrix Computations," Second Edition. Page 404-411

Author:

Peter Abeles

Constructor Summary

Constructors

Constructor and Description
SvdImplicitQr(boolean compact) Configures the class

Method Summary

Modifier and Type	Method and Description
SVDResult	_decompose(AMatrix _orig)
static SVDResult	decompose(AMatrix A, boolean compact)
AMatrix	getS()
AVector	getSingularValues()
AMatrix	getU()
AMatrix	getV()
boolean	isCompact()
int	numberOfSingularValues()
int	numCols()
int	numRows()

Methods inherited from class java.lang.Object

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

Constructor Detail

SvdImplicitQr

public SvdImplicitQr(boolean compact)

Configures the class

Parameters:

compact - Compute a compact SVD

computeU - If true it will compute the U matrix

computeV - If true it will compute the V matrix

Method Detail

decompose

public static SVDResult decompose(AMatrix A,
                                  boolean compact)

getSingularValues

public AVector getSingularValues()

numberOfSingularValues

public int numberOfSingularValues()

isCompact

public boolean isCompact()

getU

public AMatrix getU()

getV

public AMatrix getV()

getS

public AMatrix getS()

_decompose

public SVDResult _decompose(AMatrix _orig)

numRows

public int numRows()

numCols

public int numCols()