
Classes | |
| struct | AdditionalData |
Public Member Functions | |
| EigenPower (SolverControl &cn, VectorMemory< VECTOR > &mem, const AdditionalData &data=AdditionalData()) | |
| virtual | ~EigenPower () |
| template<class MATRIX > | |
| void | solve (double &value, const MATRIX &A, VECTOR &x) |
Protected Attributes | |
| AdditionalData | additional_data |
Power method (von Mises) for eigenvalue computations.
This method determines the largest eigenvalue of a matrix by applying increasing powers of this matrix to a vector. If there is an eigenvalue
with dominant absolute value, the iteration vectors will become aligned to its eigenspace and
.
A shift parameter allows to shift the spectrum, so it is possible to compute the smallest eigenvalue, too.
Convergence of this method is known to be slow.
Definition at line 50 of file eigen.h.
| EigenPower< VECTOR >::EigenPower | ( | SolverControl & | cn, |
| VectorMemory< VECTOR > & | mem, | ||
| const AdditionalData & | data = AdditionalData() |
||
| ) |
| EigenPower< VECTOR >::~EigenPower | ( | ) | [virtual] |
| void EigenPower< VECTOR >::solve | ( | double & | value, |
| const MATRIX & | A, | ||
| VECTOR & | x | ||
| ) |
Power method. x is the (not necessarily normalized, but nonzero) start vector for the power method. After the iteration, value is the approximated eigenvalue and x is the corresponding eigenvector, normalized with respect to the l2-norm.
Definition at line 240 of file eigen.h.
References Assert, deallog, StandardExceptions::ExcInternalError(), SolverControl::iterate, LogStream::pop(), LogStream::push(), SolverControl::success, and MATRIX< VECTOR >::vmult().
AdditionalData EigenPower< VECTOR >::additional_data [protected] |
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