org.ujmp.core.doublematrix.calculation.general.decomposition
Interface Eig<T>
public interface Eig<T>
Eigenvalues and eigenvectors of a real matrix.
If A is symmetric, then A = V*D*V' where the eigenvalue matrix D is diagonal
and the eigenvector matrix V is orthogonal. I.e. A =
V.times(D.times(V.transpose())) and V.times(V.transpose()) equals the
identity matrix.
If A is not symmetric, then the eigenvalue matrix D is block diagonal with
the real eigenvalues in 1-by-1 blocks and any complex eigenvalues, lambda +
i*mu, in 2-by-2 blocks, [lambda, mu; -mu, lambda]. The columns of V represent
the eigenvectors in the sense that A*V = V*D, i.e. A.times(V) equals
V.times(D). The matrix V may be badly conditioned, or even singular, so the
validity of the equation A = V*D*inverse(V) depends upon V.cond().
Method Summary |
T[] |
calc(T source)
|
THRESHOLD
static final int THRESHOLD
- See Also:
- Constant Field Values
MATRIX
static final Eig<Matrix> MATRIX
MATRIXLARGESINGLETHREADED
static final Eig<Matrix> MATRIXLARGESINGLETHREADED
MATRIXLARGEMULTITHREADED
static final Eig<Matrix> MATRIXLARGEMULTITHREADED
INSTANCE
static final Eig<Matrix> INSTANCE
UJMP
static final Eig<Matrix> UJMP
MATRIXSMALLMULTITHREADED
static final Eig<Matrix> MATRIXSMALLMULTITHREADED
MATRIXSMALLSINGLETHREADED
static final Eig<Matrix> MATRIXSMALLSINGLETHREADED
calc
T[] calc(T source)
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