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NonLinearLeastSquare Class Reference#include <leastsquare.hpp>
Detailed DescriptionDefault least square method using a given optimization algorithm (default is conjugate gradient).min { r(x) : x in R^n } where r(x) = ||f(x)||^2 the euclidian norm of f(x) for some vector-valued function f from R^n to R^m f = (f1, ..., fm) with fi(x) = bi - phi(x,ti) where bi is the vector of target data and phi is a scalar function. Assuming the differentiability of f, the gradient of r is define by grad r(x) = f'(x)^t.f(x) Array vector class has the requirement of the previous class Handle class is need to manage pointer to optimization method
The documentation for this class was generated from the following file:
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