Weighted progressive iteration approximation and convergence analysis

  • Authors:
  • Lizheng Lu

  • Affiliations:
  • Department of Mathematics, Zhejiang Gongshang University, Hangzhou 310018, PR China

  • Venue:
  • Computer Aided Geometric Design
  • Year:
  • 2010

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Abstract

We present a new and efficient method for weighted progressive iteration approximations of data points by using normalized totally positive bases. Compared to the usual progressive iteration approximation, our method has a faster convergence rate for any normalized totally positive basis, which is achieved by choosing an optimal value for the weight. For weighted progressive iteration approximations, we prove that the normalized B-basis of a space provides the fastest convergence rate among all normalized totally positive bases of the space. These results are also valid for tensor product surfaces.