public override Vector values(Vector x)
{
// dummy nested optimization
Vector coefficients = new Vector(3, 1.0);
OneDimensionalPolynomialDegreeN oneDimensionalPolynomialDegreeN = new OneDimensionalPolynomialDegreeN(coefficients);
NoConstraint constraint = new NoConstraint();
Vector initialValues = new Vector(1, 100.0);
Problem problem = new Problem(oneDimensionalPolynomialDegreeN, constraint, initialValues);
LevenbergMarquardt optimizationMethod = new LevenbergMarquardt();
//Simplex optimizationMethod(0.1);
//ConjugateGradient optimizationMethod;
//SteepestDescent optimizationMethod;
EndCriteria endCriteria = new EndCriteria(1000, 100, 1e-5, 1e-5, 1e-5);
optimizationMethod.minimize(problem, endCriteria);
// return dummy result
Vector dummy = new Vector(1, 0);
return(dummy);
}
public override Vector values(Vector x)
{
// dummy nested optimization
Vector coefficients = new Vector(3, 1.0);
OneDimensionalPolynomialDegreeN oneDimensionalPolynomialDegreeN = new OneDimensionalPolynomialDegreeN(coefficients);
NoConstraint constraint = new NoConstraint();
Vector initialValues = new Vector(1, 100.0);
Problem problem = new Problem(oneDimensionalPolynomialDegreeN, constraint, initialValues);
LevenbergMarquardt optimizationMethod = new LevenbergMarquardt();
//Simplex optimizationMethod(0.1);
//ConjugateGradient optimizationMethod;
//SteepestDescent optimizationMethod;
EndCriteria endCriteria = new EndCriteria(1000, 100, 1e-5, 1e-5, 1e-5);
optimizationMethod.minimize(problem, endCriteria);
// return dummy result
Vector dummy = new Vector(1,0);
return dummy;
}
