java.io.Serializable
public class SingularValueDecomposition
extends java.lang.Object
implements java.io.Serializable
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 | Description |
---|---|
SingularValueDecomposition(Matrix Arg) |
Construct the singular value decomposition.
|
Modifier and Type | Method | 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
|
public SingularValueDecomposition(Matrix Arg)
Arg
- Rectangular matrixpublic Matrix getU()
public Matrix getV()
public double[] getSingularValues()
public Matrix getS()
public double norm2()
public double cond()
public int rank()