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IRLS(derived) OPTIMIZATION ALGORITHMS IRLS(derived) Jun 1 15:18NAME Irls - Iterative reweighted least squaresSYNOPSIS #include <Irls.hh> class IterativeReweightedLS : public QuadraticOptima \fIPublic members\fP IterativeReweightedLS(int, LinearForward*, Vector<double>*, int, int, int, double, double); IterativeReweightedLS(int, LinearForward*, Vector<double>*, int, int, int, double, double, int); ~IterativeReweightedLS(); Model<double> optimizer(Model<double>&); Model<long> optimizer(Model<long>&); \fIPrivate members\fP PreconditionedCGLS* pcgls; DiagMatrix<double>* weight; double taper; int niterWeight; int order; void updateWeight(Vector<double>&);DESCRIPTION IterativeReweightedLS() This algorithm gives you the flexibility to choose different norms (other than the norm 2) to solve linear systems. A comprehensible description of this method can be found in "Robust methods in inverse theory", 1988, Inverse Problems 4, by J. Scales and A. Gersztenkorn.DESCRIPTION Constructors: IterativeReweightedLS(int ???, LinearForward* ???, Vector<double>* ???, int ???, int ???, int ???, double ???, double ???); ???... Methods: optimizer(Model<double>&) model0: Initial model for the Irls procedure. The optimum model is returned by the function.CAVEATS This procedure is still under development. DEFINED MACROS IRLS_HHINCLUDED FILES "PreCGLS.hh"SOURCE FILES Irls.cc
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