Newton's iteration method has found its application in many research
areas for solving a great variety of problems. However, it
has one signicant drawback - its convergence to the root depends
on the initial guess, which must lie in the vicinity of the root. If
the initial guess is not chosen properly, Newton's iteration method may converge to a wrong intersection or not converge at all. An approach for identifying regions of parameter space of a surface in which Newton's iteration method is guaranteed to converge to a unique solution has been proposed [Toth 1985], but it is very time consuming, and therefore not practical. Some other improvements have also been applied [Barth and St¨urzlinger 1993; Qin et al. 1997] to reduce the probability of reporting wrong intersections, but neither of them gives 100% guarantee of the right convergence. Therefore, visual artifacts can still be observed, especially along the surface silhouettes.
Newton's iteration method has found its application in many research
areas for solving a great variety of problems. However, it
has one signicant drawback - its convergence to the root depends
on the initial guess, which must lie in the vicinity of the root. If
the initial guess is not chosen properly, Newton's iteration method may converge to a wrong intersection or not converge at all. An approach for identifying regions of parameter space of a surface in which Newton's iteration method is guaranteed to converge to a unique solution has been proposed [Toth 1985], but it is very time consuming, and therefore not practical. Some other improvements have also been applied [Barth and St¨urzlinger 1993; Qin et al. 1997] to reduce the probability of reporting wrong intersections, but neither of them gives 100% guarantee of the right convergence. Therefore, visual artifacts can still be observed, especially along the surface silhouettes.
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