A computational method for the solution of dierential equations is proposed. With this method an accurate approximation is built by incremental additions of optimal local basis functions. The parallel direct search software package (PDS), that supports parallel objective function evaluations, is use
A basis function for approximation and the solutions of partial differential equations
β Scribed by H. Y. Tian; S. Reutskiy; C. S. Chen
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 415 KB
- Volume
- 24
- Category
- Article
- ISSN
- 0749-159X
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β¦ Synopsis
Abstract
In this article, we introduce a type of basis functions to approximate a set of scattered data. Each of the basis functions is in the form of a truncated series over some orthogonal system of eigenfunctions. In particular, the trigonometric eigenfunctions are used. We test our basis functions on recovering the wellβknown Franke's and Peaks functions given by scattered data, and on the extension of a singular function from an irregular domain onto a square. These basis functions are further used in Kansa's method for solving Helmholtzβtype equations on arbitrary domains. Proper one level and two level approximation techniques are discussed. A comparison of numerical with analytic solutions is given. The numerical results show that our approach is accurate and efficient. Β© 2007 Wiley Periodicals, Inc. Numer Methods Partial Differential Eq, 2008
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