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java.lang.Objectmath.linearAlgebra.SingularValueDecomposition
public class SingularValueDecomposition
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.
| Constructor Summary | |
|---|---|
| SingularValueDecomposition(Matrix Arg)Construct the singular value decomposition | |
| Method Summary | |
|---|---|
|  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 | 
| Methods inherited from class java.lang.Object | 
|---|
| equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait | 
| Constructor Detail | 
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public SingularValueDecomposition(Matrix Arg)
Arg - Rectangular matrix
          Structure to access U, S and V.| Method Detail | 
|---|
public Matrix getU()
public Matrix getV()
public double[] getSingularValues()
public Matrix getS()
public double norm2()
public double cond()
public int rank()
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