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 static double |
EPS |
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 |
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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 static final double EPS
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()
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