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 decompostion always exists, so the constructor will never fail. The matrix condition number and the effective numerical rank can be computed from this decomposition.
| Constructor and Description |
|---|
SingularValueDecomposition(double[][] Arg)
Construct the singular value decomposition
|
| Modifier and Type | Method and Description |
|---|---|
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
|
public SingularValueDecomposition(double[][] Arg)
Arg - Rectangular matrixpublic double[][] getU()
public double[][] getV()
public double[] getSingularValues()
public double[][] getS()
public double norm2()
public double cond()
public int rank()
Jas4pp 1.5 © Java Analysis Studio for Particle Physics