
public class SingularValueDecomposition extends Object
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 decomposition always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.
| Modifier and Type | Field and Description | 
|---|---|
private int | 
m
Row and column dimensions. 
 | 
private int | 
n
Row and column dimensions. 
 | 
private double[] | 
s
Array for internal storage of singular values. 
 | 
private double[][] | 
U
Arrays for internal storage of U and V. 
 | 
private double[][] | 
V
Arrays for internal storage of U and V. 
 | 
| Constructor and Description | 
|---|
SingularValueDecomposition(double[][] Arg)
Constructor. 
 | 
SingularValueDecomposition(Matrix Arg)
Construct the singular value decomposition 
 | 
| Modifier and Type | Method and Description | 
|---|---|
double | 
cond()
Two norm condition number 
 | 
Matrix | 
getS()
Return the diagonal matrix of singular values 
 | 
double[] | 
getSingularValues()
Return the one-dimensional array of singular values 
 | 
Matrix | 
getU()
Return the left singular vectors 
 | 
Matrix | 
getV()
Return the right singular vectors 
 | 
double | 
norm2()
Two norm 
 | 
int | 
rank()
Effective numerical matrix rank 
 | 
private double[][] U
private double[][] V
private double[] s
private int m
private int n
public SingularValueDecomposition(Matrix Arg)
Arg - Rectangular matrixpublic SingularValueDecomposition(double[][] Arg)
Arg - Rectangular input matrixpublic Matrix getU()
public Matrix getV()
public double[] getSingularValues()
public Matrix getS()
public double norm2()
public double cond()
public int rank()