HLIBpro
2.9.1

Defines interface for all ACA algorithms and implements classical ACA. More...
#include <TLowRankApx.hh>
Public Member Functions  
virtual TMatrix *  build (const TBlockCluster *cl, const TTruncAcc &acc) const 
virtual TMatrix *  build (const TBlockIndexSet &block_is, const TTruncAcc &acc) const 
virtual bool  has_statistics () const 
indicate if algorithm provides statistics  
Adaptive cross approximation (ACA) is a heuristic for computing a low rank approximation of a given dense matrix by successively removing specific pairs of rows and columns (crosses) from the matrix until the rest is below some threshold (defined by blockwise accuracy). Due to the algorithm, only the matrix coefficients in form of a TCoeffFn are needed, permitting the straightforward adaption of existing implementations for the construction of Hmatrices. The costs are linear in the dimension of the block and quadratic in the rank.

virtual 
build low rank matrix for block cluster bct with rank defined by accuracy acc
Reimplemented from TLowRankApx.

virtual 
build low rank matrix for block index set block_is with rank defined by accuracy acc
Implements TLowRankApx.