On convergent numerical algorithms for unsymmetric collocation

被引:33
作者
Lee, Cheng-Feng [1 ]
Ling, Leevan [2 ]
Schaback, Robert [3 ]
机构
[1] Natl Sun Yat Sen Univ, Dept Appl Math, Kaohsiung 80424, Taiwan
[2] Hong Kong Baptist Univ, Dept Math, Kowloon, Hong Kong, Peoples R China
[3] Univ Gottingen, Inst Numer & Angew Math, D-37083 Gottingen, Germany
关键词
Radial basis function; Kansa's method; Convergence; Error bounds; Linear optimization; Effective condition number; High precision computation; RADIAL BASIS FUNCTIONS; PARTIAL-DIFFERENTIAL-EQUATIONS; EFFECTIVE CONDITION NUMBER; COMPUTATIONAL FLUID-DYNAMICS; DATA APPROXIMATION SCHEME; BOUNDARY-VALUE-PROBLEMS; MULTIVARIATE INTERPOLATION; MULTIQUADRICS; PARAMETER;
D O I
10.1007/s10444-008-9071-x
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
In this paper, we are interested in some convergent formulations for the unsymmetric collocation method or the so-called Kansa's method. We review some newly developed theories on solvability and convergence. The rates of convergence of these variations of Kansa's method are examined and verified in arbitrary-precision computations. Numerical examples confirm with the theories that the modified Kansa's method converges faster than the interpolant to the solution; that is, exponential convergence for the multiquadric and Gaussian radial basis functions (RBFs). Some numerical algorithms are proposed for efficiency and accuracy in practical applications of Kansa's method. In double-precision, even for very large RBF shape parameters, we show that the modified Kansa's method, through a subspace selection using a greedy algorithm, can produce acceptable approximate solutions. A benchmark algorithm is used to verify the optimality of the selection process.
引用
收藏
页码:339 / 354
页数:16
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