A Quasi-Newton Method for Unconstrained Minimization Problems.
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WISCONSIN UNIV MADISON MATHEMATICS RESEARCH CENTER
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A method is described for the minimization of a function Fx of n variables. Convergence to a stationary point is shown without assumptions on second order derivatives. If the sequence generated by this method has a cluster point in a neighbourhood of which Fx is twice continuously differentiable and has a positive definite Hessian matrix, then the convergence is superlinear. It is shown that under appropriate assumptions n consecutive search directions are conjugate. No computation of second order derivatives is required.
- Numerical Mathematics