javax.robotics.vecmath.jama
Class SingularValueDecomposition

java.lang.Object
  javax.robotics.vecmath.jama.SingularValueDecomposition

All Implemented Interfaces:

java.io.Serializable

public class SingularValueDecomposition
extends java.lang.Object
implements java.io.Serializable

Singular Value Decomposition.

For an m-by-n matrix A with m >= n, the singular value decomposition is an m-by-n orthogonal matrix U, an 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.

See Also:

Serialized Form

Constructor Summary

SingularValueDecomposition(double[][] Arg, int NumRow, int NumCol)
Construct the singular value decomposition

Method Summary

double	cond() Two norm condition number
double[][]	getS() Return the diagonal matrix of singular values
double[]	getSingularValues() Return the one-dimensional array of singular values
double[][]	getU() Return the left singular vectors
double[][]	getV() Return the right singular vectors
double	norm2() Two norm
int	rank() Effective numerical matrix rank

Methods inherited from class java.lang.Object

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

Constructor Detail

SingularValueDecomposition

public SingularValueDecomposition(double[][] Arg,
                                  int NumRow,
                                  int NumCol)

Construct the singular value decomposition

Parameters:

Arg - Rectangular matrix

NumRow - number of rows of matrix

NumCol - number of columns of matrix

Method Detail

getU

public final double[][] getU()

Return the left singular vectors

Returns:

U

getV

public final double[][] getV()

Return the right singular vectors

Returns:

V

getSingularValues

public final double[] getSingularValues()

Return the one-dimensional array of singular values

Returns:

diagonal of S.

getS

public double[][] getS()

Return the diagonal matrix of singular values

Returns:

S

norm2

public final double norm2()

Two norm

Returns:

max(S)

cond

public double cond()

Two norm condition number

Returns:

max(S)/min(S)

rank

public int rank()

Effective numerical matrix rank

Returns:

Number of nonnegligible singular values.