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authors Fang, Lian and Gossard, David C.
year 1995
title Multidimensional curve fitting to unorganized data points by nonlinear minimization
source Computer-Aided Design, Vol. 27 (1) (1995) pp. 48-58
summary Many papers have addressed the problem of fitting curves to data points. However, most of the approaches are subject to a restriction that the data points must be ordered.The paper presents a method for generating a piecewise continuous parametric curve from a set of unordered and error-filled data points. The resulting curve not only providesa good fit to the original data but also possesses good fairness. Excluding the endpoints of the curve, none of the connectivity information needs to be specified, thuseliminating the necessity of an initial parameterization. The standard regularization method for univariate functions is modified for multidimensional parametric functions andresults in a nonlinear minimization problem. Successive quadratic programming is applied to find the optimal solution. A physical model is also supplied to facilitate anintuitive understanding of the mathematical background.
keywords Data Interpolation, Regularization, Nonlinear Minimization
series journal paper
references Content-type: text/plain
last changed 2003/05/15 19:33
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