class IterativeReweightedLS : public QuadraticOptima

Iterative reweighted least squares

Inheritance:

public members:

IterativeReweightedLS ( int n , LinearForward * p , Vector <double>* data, int lp, int w_nit, int nit, double tape, double tol , int verb)
a constructor
int n
dimension of model space
LinearForward * p
pointer to the forward operator (matrix)
Vector <double>* data
observed data vector
int lp
lp norm
int w_nit
number of out-loop iterations
int nit
maximum number of iterations in solving linear system
double tape
a parameter
double tol
the maxmimum toleratable error
int verb
verbose or quiet
IterativeReweightedLS (int n , LinearForward * p , Vector <double>* data, int lp, int w_nit, int nit, double tape, double tol )
a constructor
Model <double> optimizer ( Model <double>& m0)
IRLS search starting from m0, returns an optimum model
Model <long> optimizer ( Model <long>& m0)
IRLS search starting from m0, returns an optimum model

Inherited from QuadraticOptima:

public members:

virtual int numIterations()
Vector <double> currentError()

Inherited from Optima:

protected members:

int iterMax
double tol
List <double>* residue
ObjectiveFunction * fp
int isVerbose
int isSuccess
List <double> appendResidue(double res)

Documentation

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.

This procedure is not fully tested at the current stage.

this class has no child classes.

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(c)opyright by Malte Zöckler, Roland Wunderling