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java.lang.Object | +--Jama.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 |
clone,
equals,
finalize,
getClass,
hashCode,
notify,
notifyAll,
toString,
wait,
wait,
wait |
Constructor Detail |
public SingularValueDecomposition(Matrix Arg)
A
- Rectangular matrixMethod 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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