Applications of the Conjugate Gradient method in optimal surface parameterizations

作者：Jia Zhongxiao^*

来源：International Journal of Computer Mathematics, 2010, 87(5): 1032-1039.

DOI：10.1080/00207160802275951

• symmetric seimidefinite
• positive definite
• CG
• Krylov subspace
• surface parameterization

This paper concerns the solutions of very large symmetric semipositive definite ( singular) linear systems involved in the problem of optimal surface parameterizations using inverse curvature mapping. Two approaches are presented that transform the singular linear systems into two kinds of symmetric positive definite linear systems, so that the famous Conjugate Gradient (CG) method can be used for solving them. Numerical experiments are run on two practical large problems to illustrate that the CG algorithm works very efficiently.

• 出版日期2010
• 单位清华大学