class PreconditionedCGLS : public LSConjugateGradient

Pre-conditioned Conjugate Gradient for Least Squares

Inheritance:


public members:

PreconditionedCGLS ( int n , LinearForward * p , Vector <double>* data, int it, 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 it
maximum number of iterations in solving linear system
double tol
the maxmimum toleratable error
int verb
vebose or quiet
PreconditionedCGLS (int n , LinearForward * p , Vector <double>* data, int it, double tol )
a constructor
void assignWeight ( DiagMatrix <double>& d)
assign the pre-conditioning diagonal matrix
Model <double> optimizer ( Model <double>& m0)
Preconditioned LS Conjugate gradient starting from m0, returns an optimum Model
Model <long> optimizer ( Model <long>& m0)
Preconditioned LS Conjugate gradient starting from m0, returns an optimum Model

Inherited from LSConjugateGradient:

public members:

Model <double> optimizer( Model <double>& m0)
Model <long> optimizer( Model <long>& m0)

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

PreconditionedCGLS() This is a class almost identical to that of CGLS, but it handles some preconditioned algorithms. Currently, PreconditionedCGLS is actually used as the front-end of CGLS for Irls, since Irls reduces to a sequence of conditioned CGLS.

this class has no child classes.

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(c)opyright by Malte Zöckler, Roland Wunderling