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levenberg-marquart optimization algorithm: -- for a vector function F: R^n -> R^m the goal is to minimize the function f(x)=norm(F(x))^2 --at a given point x the levmar-step d is given by: (J*J_tr+lambda*I)d=-J_tr*F(x) where J is the jacobian of F
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levenberg-marquart optimization algorithm:
-- for a vector function F: R^n -> R^m the algorithm is to minimizes the function
f(x)=( norm(F(x)) )^2
--at a given point x the levmar-step d is given by:
(J_J_tr+lambda_I)d=-J_tr*F(x)
where J is the jacobian of F